Displacement Lens [JOAT]Displacement Lens
Introduction
The Displacement Lens is an advanced open-source momentum analysis indicator that measures real-time displacement intensity by fusing four normalized momentum oscillators with volume-weighted candle body analysis. It produces a composite displacement score displayed as a gradient histogram with adaptive threshold bands, designed to separate institutional displacement candles from retail noise. This is not a simple oscillator mashup — it is a unified displacement measurement engine with institutional-grade features built on top of the core signal.
The indicator operates in its own pane (non-overlay) and provides traders with a clear, visual representation of when price is being displaced by institutional force versus when it is drifting on low-conviction retail flow.
Why This Indicator Exists
Standard momentum oscillators like RSI, CCI, or Bollinger %B each capture only one dimension of market momentum. Traders often flip between multiple oscillators trying to get a complete picture. The Displacement Lens solves this by:
Normalizing four independent oscillators (BB %B, CCI, ROC, RSI) to a common scale so they can be meaningfully combined
Weighting the composite by volume intensity and candle body ratio — because a large-bodied candle on high volume is institutional displacement, while a small-bodied candle on low volume is noise
Adding adaptive threshold bands that adjust to the signal's own volatility, rather than using fixed overbought/oversold levels that fail in different market conditions
Layering institutional features on top: decay detection, accumulation phases, divergence scanning, exhaustion markers, and a per-bar institutional candle grade
The result is a single composite signal that tells you not just "is momentum bullish or bearish" but "how strong is the institutional displacement right now, and is it accelerating, decaying, or exhausting?"
Core Signal Construction
The displacement signal is built in three stages:
Stage 1: Oscillator Normalization
Each of the four oscillators is normalized to a range using methods appropriate to each:
Bollinger %B: Measures where price sits within the Bollinger Bands. The raw %B (0 to 1) is remapped to with a soft clamp. When price is above the upper band, the score approaches +1. Below the lower band, it approaches -1.
CCI: The Commodity Channel Index is divided by 200 and clamped. CCI values beyond +/-200 saturate at +/-1, while values near zero produce scores near zero.
ROC: Rate of Change is normalized using adaptive scaling — it divides by twice its own standard deviation over 50 bars. This means the normalization adapts to the instrument's typical momentum range.
RSI: Remapped from the standard 0-100 range to by subtracting 50 and dividing by 50. RSI 70 becomes +0.4, RSI 30 becomes -0.4.
Each oscillator can be individually toggled on or off, and the composite averages only the active ones.
Stage 2: Volume-Weighted Displacement
The oscillator composite is blended with a volume displacement component:
float vol_displacement = disp_direction * body_ratio * vol_intensity
float raw_signal = osc_composite * (1.0 - vol_weight) + vol_displacement * vol_weight
Where:
disp_direction is +1 for bullish candles, -1 for bearish
body_ratio is the candle body size divided by the full range (high-low) — institutional candles have ratios above 0.7
vol_intensity is current volume relative to the 20-bar average, clamped to
vol_weight (default 0.3) controls how much volume influences the final score
This means a strong oscillator reading on a small-bodied, low-volume candle gets dampened, while a moderate oscillator reading on a large-bodied, high-volume candle gets amplified.
Stage 3: Smoothing and Thresholds
The raw signal is smoothed with an EMA (default period 5), and adaptive threshold bands are calculated as the signal's own standard deviation multiplied by a configurable factor (default 1.5x over 100 bars). This creates bands that widen in volatile markets and tighten in calm markets — far more reliable than fixed thresholds.
Institutional Features
1. Displacement Impulse Signals
When the signal crosses above the upper threshold for the first time (with volume and body confirmation), a bullish impulse label appears. Similarly for bearish. These mark the exact moment institutional displacement begins — not after it has already played out.
2. Momentum Divergence Engine
The indicator detects four types of divergence between price pivots and signal pivots:
Regular Bearish: Price makes a higher high, but the displacement signal makes a lower high — momentum is weakening despite price advance
Regular Bullish: Price makes a lower low, but the signal makes a higher low — selling pressure is fading
Hidden Bearish: Price makes a lower high, but the signal makes a higher high — continuation of downtrend likely
Hidden Bullish: Price makes a higher low, but the signal makes a lower low — continuation of uptrend likely
Divergences are detected using configurable pivot lengths and drawn as labeled markers directly on the histogram.
3. Displacement Decay Zones
When the signal was above the upper threshold but starts declining (still positive, but fading), the indicator marks a "decay zone" — a dotted box on the histogram showing where institutional momentum is waning. This is a unique concept: it identifies the transition from impulse to drift before the signal crosses zero. Bear decay zones work identically on the downside.
4. Accumulation Phase Detector
When both the signal and signal line are near zero (below half the standard deviation) for a minimum number of bars, the indicator draws a dashed "accumulation" box. These low-displacement consolidation phases often precede the next major impulse move. The concept is borrowed from Wyckoff methodology but applied to displacement scoring rather than price.
5. Institutional Candle Grading
Every bar receives a grade from D to A+ based on three factors:
Body ratio (how much of the candle is body vs wick) — 33.3% weight
Volume intensity (current volume vs 20-bar average) — 33.3% weight
Displacement alignment (how far the signal is from the threshold) — 33.4% weight
A+ candles (score >= 80) with body ratio > 0.7 and volume > 1.5x average are flagged as true institutional candles. The grade is shown in the dashboard.
6. Velocity Channel
The rate of change of the displacement signal itself is plotted as a velocity line with standard deviation bands. When velocity is expanding (accelerating), the displacement move has conviction. When velocity contracts, the move is losing steam. Optional glow effects make the velocity channel visually distinct.
7. Exhaustion Detection
Bullish exhaustion fires when the signal was above the threshold for 3 consecutive bars and then declines for 3 consecutive bars. Bearish exhaustion is the mirror. These are rare, high-conviction reversal signals that mark the exact point where institutional displacement has peaked and is reversing.
8. HTF Displacement Bias
The indicator calculates the same displacement composite on a higher timeframe (default 4H) using request.security(). When the current timeframe signal aligns with the HTF bias, conviction is higher. The dashboard shows whether HTF is BULLISH, BEARISH, or NEUTRAL and whether it is aligned with the current signal.
9. Displacement Streak Counter
Tracks how many consecutive bars the signal has been above the upper threshold (bull streak) or below the lower threshold (bear streak). Longer streaks indicate sustained institutional pressure.
Visual Elements
Gradient Histogram: The main displacement signal plotted as columns with gradient coloring — bullish bars transition from muted teal to bright teal as strength increases, bearish bars from muted rose to hot rose. Volume spike bars are highlighted in amber.
Signal Line: A further-smoothed version of the signal (3x the smoothing period) plotted as a bright lavender line. Crossovers between the signal and signal line generate diamond markers.
Adaptive Threshold Bands: Upper and lower threshold lines that expand and contract with signal volatility.
Decay Zones: Dotted boxes marking fading institutional momentum.
Accumulation Zones: Dashed boxes marking low-displacement consolidation.
Velocity Channel: Rate-of-change line with glow bands showing displacement acceleration.
15-Row Dashboard: Comprehensive command center showing Signal value, Phase classification, Candle Grade, HTF Bias, Streak, Velocity, Divergence status, and more.
Input Parameters
Oscillator Components:
BB Length (default 20), BB Multiplier (default 2.0)
CCI Length (default 23), ROC Length (default 50), RSI Length (default 14)
Individual toggles for each oscillator
Displacement Engine:
Signal Smoothing (default 5) — EMA period for the final signal
Volume Weight (default 0.3) — how much volume influences the score
Threshold Lookback (default 100) — period for adaptive threshold calculation
Threshold Multiplier (default 1.5) — sensitivity of threshold bands
Institutional Features:
Toggles for Impulse Signals, Divergences, Decay Zones, Accumulation Phases, Signal Crossovers, Velocity Channel, Exhaustion Markers, HTF Bias
HTF Timeframe (default 240 / 4H)
Accumulation Min Bars (default 8), Decay Min Bars (default 5)
Max Boxes (default 30), Divergence Pivot Length (default 5)
How to Use This Indicator
Step 1: Read the Phase
The dashboard shows the current displacement phase: IMPULSE BULL, IMPULSE BEAR, DRIFT BULL, DRIFT BEAR, DECAY, ACCUMULATION, or FLAT. This tells you the market's current displacement state at a glance.
Step 2: Watch for Impulse Signals
When the signal crosses the threshold with volume confirmation, an impulse label appears. These are the highest-conviction displacement events — institutional money is moving price.
Step 3: Monitor Decay and Exhaustion
After an impulse, watch for decay zones forming. If the signal was strong and starts declining, the move is losing institutional backing. Exhaustion markers confirm the reversal point.
Step 4: Confirm with HTF Bias
Check whether the HTF displacement aligns with the current timeframe. Aligned signals have higher follow-through probability.
Step 5: Use Divergences for Reversals
Regular divergences warn of potential reversals. Hidden divergences confirm trend continuation. Both are detected automatically.
Step 6: Identify Accumulation for Breakout Setups
When the indicator marks an accumulation phase (low displacement for extended bars), prepare for the next impulse. The breakout direction is often confirmed by the first impulse signal after accumulation ends.
Limitations
The indicator measures displacement intensity, not price direction prediction. Strong displacement can occur in both breakouts and fakeouts.
Volume data quality varies by instrument and exchange. Forex volume on TradingView represents tick volume, not true volume.
HTF bias uses request.security() which may produce different results on different chart types.
Divergence detection requires sufficient pivot history — it will not fire on the first few hundred bars of a chart.
Exhaustion signals are intentionally rare (require 3 bars above threshold + 3 bars declining). They may not fire in fast-moving markets.
The indicator works best on liquid instruments with consistent volume patterns.
Past displacement patterns do not guarantee future price movement.
Originality Statement
This indicator is original in its unified displacement measurement approach. While individual oscillators (BB %B, CCI, ROC, RSI) are well-known, this indicator is justified because:
It normalizes four oscillators to a common scale using methods appropriate to each (adaptive scaling for ROC, division-based for CCI, remapping for RSI and BB %B) — not simply averaging raw values
The volume-weighted displacement component integrates candle body analysis with volume intensity, creating a measure that distinguishes institutional candles from retail noise
Adaptive threshold bands based on the signal's own standard deviation replace unreliable fixed thresholds
The Displacement Decay Zone concept — identifying the transition from impulse to drift before the signal crosses zero — is not available in standard oscillators
The Accumulation Phase Detector applies Wyckoff-inspired consolidation detection to a composite momentum score rather than price
The Institutional Candle Grading system scores every bar on three dimensions simultaneously (body, volume, displacement alignment)
The Velocity Channel measures the rate of change of displacement itself — a second derivative that reveals acceleration and deceleration of institutional activity
The combination of all these features with a comprehensive dashboard creates a unified displacement analysis system not available in any single existing indicator
Disclaimer
This indicator is provided for educational and informational purposes only. It is not financial advice or a recommendation to buy or sell any financial instrument. Trading involves substantial risk of loss and is not suitable for all investors.
The displacement signal measures momentum intensity based on mathematical calculations of current and historical market data. It does not predict future price movement. High displacement does not guarantee profitable trades. Past displacement patterns do not guarantee future patterns.
Always use proper risk management, including stop losses and position sizing appropriate for your account size and risk tolerance. Never risk more than you can afford to lose.
The author is not responsible for any losses incurred from using this indicator. Users assume full responsibility for all trading decisions.
-Made with passion by officialjackofalltrades
インジケーター
Multi-Asset SuperTrend Map [BigBeluga]🔵 OVERVIEW
Multi-Asset SuperTrend Map is a comparative market-structure visualization tool that displays multiple assets side-by-side using a unified SuperTrend framework.
Instead of switching charts or stacking indicators, this tool compresses several markets into a single view, allowing traders to instantly assess trend direction, volatility alignment, and volume pressure across assets.
Each asset is reconstructed as a scaled synthetic candle stream, aligned to the current chart’s volatility, and overlaid with its own SuperTrend logic.
🔵 CORE CONCEPT
SuperTrend as Regime Filter — Each asset uses the same ATR-based SuperTrend logic to determine bullish or bearish state.
Volatility Normalization — Assets are scaled using ATR ratios so high-price and low-price symbols can be compared visually on one chart.
Synchronized Time Axis — All assets are plotted on the current chart timeframe, enabling true bar-to-bar comparison.
Trend + Delta Context — In addition to trend direction, the indicator aggregates directional volume (delta) to reveal participation strength.
🔵 CALCULATION & LOGIC
1. SuperTrend Engine
The indicator uses TradingView’s native SuperTrend calculation:
= ta.supertrend(factor, atrPeriod)
ATR Length controls volatility smoothing.
ATR Factor defines band width and trend sensitivity.
Trend direction is binary:
Bullish when price is above the SuperTrend line.
Bearish when price is below the SuperTrend line.
2. Multi-Asset Scaling Logic
Each external symbol is fetched using request.security() .
ATR is calculated both on the chart symbol and the external symbol.
A scaling coefficient is derived:
chart ATR ÷ symbol ATR
// --- compute scale factor on SAME timeframe
atrChart = ta.atr(200)
atrSym2 = request.security(sym, timeframe.period, ta.atr(200))
k = atrSym2 != 0.0 ? atrChart / atrSym2 : 1.0
All OHLC values are remapped so different assets share a comparable vertical range.
3. Synthetic Candle Reconstruction
Each asset is redrawn using:
Vertical lines for wicks
Thick lines for candle bodies
Candle color logic:
Trend-based (SuperTrend direction) if enabled
Otherwise standard bullish/bearish candle logic
4. SuperTrend Mapping
The SuperTrend line for each asset is remapped and drawn as a polyline.
This allows trend curvature and regime shifts to be compared visually across symbols.
5. Delta Volume Aggregation
Directional volume is accumulated:
Volume added when close > open
Volume subtracted when close < open
Delta is displayed per asset, showing whether bullish or bearish participation dominates.
🔵 VISUAL STRUCTURE
Each asset is wrapped inside a bounding box representing its full recent range.
Background color reflects current trend direction (bullish or bearish).
Asset label displays:
Symbol name
Current price
Trend direction arrow (▲ / ▼)
Delta volume is displayed beneath the asset block for flow context.
⚠️MARKET SESSION BEHAVIOR
On lower timeframes (e.g. 1m–12h), traditional stock markets are closed during weekends .
During these periods, price data may appear as flat or static candles with minimal or no movement.
This is expected behavior and reflects the absence of active trading, not a calculation error.
Crypto markets remain unaffected and continue updating normally.
🔵 HOW TO USE
Compare trend alignment across correlated markets (e.g., BTC vs ETH).
Identify relative strength when one asset trends while others stall.
Use delta volume to confirm whether trends are supported by participation.
Spot early divergence when price trends align but delta disagrees.
Combine with higher-timeframe structure or liquidity tools for execution.
🔵 CONCLUSION
Multi-Asset SuperTrend Map transforms SuperTrend from a single-market indicator into a cross-market decision framework .
By normalizing volatility, synchronizing time, and adding volume delta context, it enables traders to evaluate trend quality, alignment, and participation across assets — all from one chart.
This makes it especially powerful for crypto pairs, index baskets, and correlated markets where relative behavior matters as much as absolute price direction. インジケーター
インジケーター
Turbulence Fractal Scanner [JOAT]Turbulence Fractal Scanner
Introduction
The Turbulence Fractal Scanner is an advanced open-source volatility chaos prediction engine that combines ATR, Bollinger Band Width, Keltner Channels, Historical Volatility, and Squeeze detection into a unified volatility analysis system. This indicator measures market turbulence across multiple dimensions, creating a comprehensive volatility index that reveals expansion/contraction cycles, squeeze conditions, and breakout predictions.
Unlike single-dimension volatility indicators, the Turbulence Fractal Scanner provides multi-layered volatility intelligence through percentile ranking, composite indexing, regime classification, and squeeze detection. The indicator is designed for traders who understand that volatility precedes price movement and that multi-dimensional volatility analysis provides early warning of significant market shifts.
Why This Indicator Exists
This indicator addresses the need for comprehensive volatility analysis that goes beyond simple ATR or Bollinger Bands. By combining five distinct volatility methodologies, it reveals:
ATR Analysis: Average True Range measures actual price movement volatility
Bollinger Band Width: Measures price dispersion relative to moving average
Keltner Channels: ATR-based bands for volatility envelope detection
Historical Volatility: Statistical measure of price returns volatility
Squeeze Detection: Identifies when Bollinger Bands contract inside Keltner Channels
Composite Volatility Index: Unified measure combining all five components
Regime Classification: Categorizes volatility as Low, Normal, High, or Squeeze
Breakout Prediction: Detects squeeze breakouts with directional bias
Core Components Explained
1. ATR (Average True Range) Analysis
ATR measures the average range of price movement:
True Range: Maximum of (high - low), (high - previous close), (previous close - low)
ATR Calculation: Moving average of true range over period (default 14)
ATR Smoothing: Additional EMA smoothing (default 7) reduces noise
ATR Percent: ATR divided by close, expressed as percentage
ATR Percentile: ATR ranked against 100-bar history (0-100 scale)
ATR percentile shows whether current volatility is high or low relative to recent history. High percentile (> 70) indicates elevated volatility, low percentile (< 30) indicates compressed volatility.
2. Bollinger Band Width Analysis
BB Width measures price dispersion:
Bollinger Bands: SMA ± (standard deviation × multiplier)
BB Width: (Upper band - Lower band) / Middle band × 100
BB Width Percentile: Current width ranked against 100-bar history
Narrow BB Width indicates low volatility and potential breakout setup. Wide BB Width indicates high volatility and potential mean reversion.
3. Keltner Channel Analysis
Keltner Channels use ATR for volatility bands:
Basis: EMA of close (default 20 periods)
Range: ATR × multiplier (default 1.5)
Upper/Lower: Basis ± Range
Keltner Channels adapt to volatility changes and are used in squeeze detection.
4. Squeeze Detection
Squeeze occurs when Bollinger Bands contract inside Keltner Channels:
Squeeze On: BB Lower > KC Lower AND BB Upper < KC Upper
Squeeze Off: Bands no longer contracted
Squeeze Breakout: Transition from Squeeze On to Squeeze Off
Breakout Direction: Determined by close comparison (close > close = bullish)
Squeezes indicate extreme volatility compression. Breakouts from squeezes often lead to significant directional moves.
5. Historical Volatility (HV) Calculation
HV measures statistical volatility of returns:
Returns: Logarithmic price changes (log(close / close ))
Standard Deviation: StdDev of returns over period (default 20)
Annualization: Multiply by sqrt(252) for annual volatility (optional)
HV Percentile: Current HV ranked against 100-bar history
HV provides a statistical measure of actual price volatility, complementing the technical measures (ATR, BB Width).
6. Composite Volatility Index
All three percentile measures are combined into a unified index:
Volatility Index = (ATR Percentile + BB Width Percentile + HV Percentile) / 3
This composite index provides a balanced view of volatility across multiple methodologies. Values range from 0 (extremely low volatility) to 100 (extremely high volatility).
7. Volatility Regime Classification
The indicator classifies volatility into four regimes:
Squeeze (Priority): When squeeze is active, regardless of volatility index
Low Volatility: Volatility Index < threshold (default 30)
Normal Volatility: Volatility Index between low and high thresholds (30-70)
High Volatility: Volatility Index > threshold (default 70)
Regime classification helps traders adapt strategies to current volatility conditions.
8. Volatility Trend Analysis
The indicator tracks volatility direction:
Volatility Trend: 5-period SMA of Volatility Index
Rising Volatility: Trend rising for 3+ consecutive bars
Falling Volatility: Trend falling for 3+ consecutive bars
Expansion: Volatility Index rising for 3+ consecutive bars
Contraction: Volatility Index falling for 3+ consecutive bars
Volatility trends help predict whether turbulence is increasing or decreasing.
9. Breakout Prediction System
The indicator predicts breakouts from squeeze conditions:
Squeeze Breakout: Detected when squeeze transitions from On to Off
Direction: Bullish if close > close , bearish if close < close
Volatility Confirmation: Best breakouts occur when Volatility Index < 40 (compressed)
Breakouts from low volatility squeezes often lead to sustained directional moves.
10. Turbulence Shift Detection
The indicator identifies regime changes:
Regime Shift: When volatility regime changes (Low ↔ Normal ↔ High ↔ Squeeze)
Anti-Overlap: Minimum 10 bars between shift signals
High Vol Entry: Shift into High Volatility regime
Low Vol Entry: Shift into Low Volatility regime
Regime shifts provide early warning of changing market conditions.
Visual Elements
Volatility Index Line: Main line showing composite volatility with regime-based coloring (purple = squeeze, red = high, cyan = low, yellow = normal)
Component Lines: Three thin lines showing ATR, BB Width, and HV percentiles
Volatility Trend Line: Step-line showing smoothed volatility trend
Threshold Lines: Horizontal lines at high (70) and low (30) thresholds, plus median (50)
Zone Fills: Shaded areas above high threshold (red) and below low threshold (cyan)
Squeeze Background: Purple background when squeeze is active
Breakout Signals: Triangles marking squeeze breakouts (cyan = bullish, red/orange = bearish)
Regime Shift Circles: Small circles marking regime transitions
Information Dashboard: Displays regime, volatility index, ATR/BB/HV percentiles, squeeze status, volatility trend, expansion/contraction, breakout status, ATR/BB values, and overall signal
How to Use This Indicator
Step 1: Check Volatility Regime
Monitor the dashboard for current regime (Squeeze, Low Vol, Normal, High Vol). Adapt strategy to regime.
Step 2: Monitor Volatility Index
Volatility Index < 30 = compressed (potential breakout setup)
Volatility Index > 70 = elevated (potential mean reversion or continuation)
Step 3: Watch for Squeeze Conditions
Purple background indicates squeeze. Prepare for breakout when squeeze ends.
Step 4: Identify Breakout Direction
When squeeze breakout occurs, triangle color shows direction (cyan = bullish, red = bearish).
Step 5: Check Volatility Trend
Rising volatility = increasing turbulence, falling volatility = calming conditions.
Step 6: Monitor Expansion/Contraction
Expanding volatility often precedes strong moves. Contracting volatility suggests consolidation.
Step 7: Use Regime Shifts as Alerts
Shifts into High Vol or Low Vol regimes provide early warning of changing conditions.
Best Practices
Trade breakouts from squeeze conditions with low volatility index (< 40)
Avoid trend-following strategies in high volatility regimes (> 70)
Use low volatility regimes (< 30) to prepare for breakout setups
Monitor all three components (ATR, BB, HV) for confirmation
Rising volatility in low regime warns of impending breakout
Falling volatility in high regime suggests consolidation ahead
Combine with trend indicators - volatility shows when, trend shows direction
Be cautious of false breakouts - wait for volatility confirmation
Input Parameters
ATR Configuration:
ATR Length: Period for ATR calculation (default: 14)
ATR Smoothing: EMA smoothing period (default: 7)
Bollinger Bands:
BB Length: Period for BB calculation (default: 20)
BB Multiplier: Standard deviation multiplier (default: 2.0)
Keltner Channels:
KC Length: Period for KC basis (default: 20)
KC Multiplier: ATR multiplier for bands (default: 1.5)
Historical Volatility:
HV Length: Period for HV calculation (default: 20)
Annualize HV: Convert to annual volatility (default: enabled)
Regime Thresholds:
Low Volatility: Threshold for low regime (default: 30)
High Volatility: Threshold for high regime (default: 70)
Visual Configuration:
Low/Normal/High/Squeeze Colors: Customizable regime colors
Originality Statement
This indicator is original in its comprehensive volatility analysis approach. While individual components (ATR, BB, KC, HV, Squeeze) are established concepts, this indicator is justified because:
It combines five distinct volatility methodologies into a unified composite index
Percentile ranking normalizes all components to a common 0-100 scale
The regime classification system categorizes volatility conditions systematically
Squeeze detection with breakout prediction provides actionable trading signals
Volatility trend and expansion/contraction analysis predict volatility direction
Turbulence shift detection identifies regime changes early
The comprehensive dashboard presents all volatility dimensions simultaneously
Disclaimer
This indicator is provided for educational and informational purposes only. It is not financial advice. Trading involves substantial risk of loss. Volatility analysis does not guarantee profitable trades. Low volatility does not guarantee breakouts. High volatility does not guarantee reversals. Always use proper risk management and never risk more than you can afford to lose.
-Made with passion by officialjackofalltrades インジケーター
Prismatic Trend Matrix [JOAT]Prismatic Trend Matrix
Introduction
The Prismatic Trend Matrix is an advanced open-source multi-dimensional trend analysis system that combines Hull Moving Average, SuperTrend, ADX strength filtering, and moving average confluence into a unified trend detection engine. This indicator analyzes trend across multiple dimensions simultaneously, creating a prismatic view of market direction with gradient visualization that reveals trend strength and conviction.
Unlike single-indicator trend systems, the Prismatic Trend Matrix provides multi-layered trend intelligence through Hull MA smoothing, SuperTrend band analysis, ADX strength measurement, and EMA/SMA alignment detection. The indicator is designed for traders who understand that strong trends require confirmation across multiple analytical dimensions.
Why This Indicator Exists
This indicator addresses the need for comprehensive trend analysis that goes beyond simple moving averages. By combining four distinct trend methodologies with gradient visualization, it reveals:
Hull Moving Average: Weighted moving average with reduced lag for responsive trend detection
SuperTrend Component: ATR-based bands that identify trend direction and support/resistance
ADX Strength Filter: Measures trend strength to separate strong trends from weak/choppy conditions
Moving Average Matrix: Three EMAs and two SMAs create alignment-based trend confirmation
Trend Classification: Five-state system (Strong Bull, Weak Bull, Sideways, Weak Bear, Strong Bear)
Counter-Trend Detection: Identifies potential reversals when price moves against established trend
Prismatic Gradient: Visual fill between Hull MA and SuperTrend shows trend intensity
Core Components Explained
1. Hull Moving Average (HMA)
The Hull MA uses weighted moving averages to create a smooth trend line with minimal lag:
The calculation involves three steps:
Step 1: Calculate WMA of half-length period
Step 2: Calculate WMA of full-length period
Step 3: Calculate WMA of the difference using square root of length
The result is a moving average that responds quickly to price changes while maintaining smoothness. The indicator applies additional EMA smoothing (default 3 periods) to reduce noise.
2. SuperTrend Calculation
SuperTrend uses ATR-based bands to identify trend direction:
Source: Average of high and low (HL2)
Upper Band: Source + (ATR × Factor)
Lower Band: Source - (ATR × Factor)
Direction: Bullish when close > upper band, bearish when close < lower band
Three modes control band adjustment:
Strict Mode: Bands adjust only when price crosses or previous band is breached
Quick Mode: Bands adjust when price crosses previous band
Quicker Mode: Bands adjust immediately with price
SuperTrend provides dynamic support/resistance levels that adapt to volatility.
3. ADX Strength Measurement
The Average Directional Index measures trend strength:
DI+ (Directional Indicator Plus): Measures upward directional movement
DI- (Directional Indicator Minus): Measures downward directional movement
ADX: Smoothed average of the difference between DI+ and DI-, normalized
Threshold: ADX above threshold (default 25) indicates strong trend
Rising ADX: Indicates strengthening trend momentum
ADX filters out weak trends and choppy conditions, ensuring signals occur only during strong directional movement.
4. Moving Average Matrix
Five moving averages create a trend alignment system:
Fast EMA (9): Short-term trend direction
Medium EMA (21): Intermediate trend direction
Slow EMA (50): Primary trend direction
Fast SMA (50): Smoothed primary trend
Slow SMA (200): Long-term institutional trend
Alignment is measured by comparing the order of these averages:
Bullish Alignment: EMA9 > EMA21 > EMA50 > SMA50 (all in ascending order)
Bearish Alignment: EMA9 < EMA21 < EMA50 < SMA50 (all in descending order)
Mixed Alignment: Averages not in order (choppy or transitional conditions)
Perfect alignment indicates strong institutional conviction in the trend direction.
5. Composite Trend Classification [/b>
The indicator combines all components into a five-state trend classification:
Strong Bull (State 2): Hull rising + SuperTrend bullish + MA alignment bullish + ADX strong
Weak Bull (State 1): Hull rising + (SuperTrend bullish OR MA alignment bullish)
Sideways (State 0): Mixed signals or weak trend conditions
Weak Bear (State -1): Hull falling + (SuperTrend bearish OR MA alignment bearish)
Strong Bear (State -2): Hull falling + SuperTrend bearish + MA alignment bearish + ADX strong
This classification provides clear trend assessment at a glance.
6. Counter-Trend Detection [/b>
The indicator identifies potential reversals when price moves against established trend:
Counter-Trend Bull: Trend state neutral/bearish + close > open + price rising + DI+ > DI- + close > Hull + ADX > 20
Counter-Trend Bear: Trend state neutral/bullish + close < open + price falling + DI- > DI+ + close < Hull + ADX > 20
Counter-trend signals include anti-overlap logic to prevent signal clustering and ensure clean placement.
7. Prismatic Gradient Visualization
The indicator creates a gradient fill between Hull MA and SuperTrend:
Gradient Layers: Multiple intermediate values calculated between Hull and SuperTrend (default 15 layers)
Color Intensity: Transparency increases from Hull (solid) to SuperTrend (transparent)
Dynamic Coloring: Gradient color matches trend state (green = bullish, red = bearish, cyan = sideways)
Visual Effect: Creates a glowing prismatic effect that emphasizes trend strength
The gradient provides intuitive visual feedback on trend intensity and direction.
8. Platform Levels
Platform levels are horizontal lines at the current Hull MA value:
Extension: Lines extend forward and backward from current bar (default 7 bars each direction)
Color Coding: Platform color matches current trend state
Purpose: Provides visual reference for potential support/resistance at Hull MA level
Platforms help identify key levels where price may find support or resistance.
Visual Elements
Hull Trend Line: Thick line (3px) with regime-based coloring showing primary trend
SuperTrend Line: Medium line (2px) with step-line style showing dynamic support/resistance
EMA Matrix: Three thin lines showing fast, medium, and slow EMAs with transparency
Prismatic Gradient: Multi-layer fill between Hull and SuperTrend creating glow effect
Platform Levels: Horizontal lines at Hull MA value extending forward/backward
Counter-Trend Signals: Triangles marking potential reversal points
Background Coloring: Subtle background tint for strong bull/bear states
Information Dashboard: Displays trend state, Hull direction, ADX strength, momentum, alignment, SuperTrend, DI balance, price vs Hull, gradient zone, counter-trend status, and signal
How to Use This Indicator
Step 1: Check Trend State
Monitor the dashboard for current trend state (Strong Bull, Weak Bull, Sideways, Weak Bear, Strong Bear). Trade in the direction of strong states.
Step 2: Verify ADX Strength
Ensure ADX is above threshold (default 25) for strong trends. Low ADX indicates choppy conditions - avoid trend-following strategies.
Step 3: Confirm MA Alignment
Check if moving averages are aligned (Bullish/Bearish/Mixed). Perfect alignment confirms institutional conviction.
Step 4: Monitor Hull Direction
Hull rising = bullish bias, Hull falling = bearish bias. Hull provides the primary trend direction signal.
Step 5: Use SuperTrend for Support/Resistance
SuperTrend line acts as dynamic support in uptrends and resistance in downtrends. Breaks of SuperTrend warn of trend changes.
Step 6: Watch for Counter-Trend Signals
Counter-trend signals at extreme levels may indicate reversals. Use these cautiously and confirm with other factors.
Step 7: Assess Gradient Zone
Price in upper gradient zone (near Hull) = strong trend, price in lower zone (near SuperTrend) = weak trend or potential reversal.
Best Practices
Trade only in Strong Bull or Strong Bear states for highest probability
Avoid trading in Sideways state - wait for clear trend establishment
Use ADX as a filter - only trade when ADX > 25 for strong trends
Confirm trend with MA alignment before entering positions
Use SuperTrend as trailing stop level in trending markets
Counter-trend signals work best at extreme levels with divergence
Monitor gradient zone - price near SuperTrend may indicate trend exhaustion
Combine with higher timeframe trend for additional confirmation
Input Parameters
Hull Trend Engine:
Hull Length: Period for Hull MA calculation (default: 20)
Hull Smoothing: Additional EMA smoothing (default: 3)
SuperTrend Layer:
ATR Period: Period for ATR calculation (default: 10)
ATR Factor: Multiplier for band width (default: 3.0)
Mode: Strict, Quick, or Quicker (default: Quick)
Trend Strength:
ADX Length: Period for ADX calculation (default: 14)
ADX Smoothing: Smoothing period for ADX (default: 14)
Strength Threshold: Minimum ADX for strong trend (default: 25)
MA Matrix:
Fast EMA: Short-term EMA (default: 9)
Medium EMA: Intermediate EMA (default: 21)
Slow EMA: Primary EMA (default: 50)
Fast SMA: Smoothed primary (default: 50)
Slow SMA: Long-term institutional (default: 200)
Visual Configuration:
Bullish/Bearish Trend Colors: Customizable colors for trend states
Sideways/Weak Trend Colors: Colors for neutral and weak states
Gradient Layers: Number of gradient fills (default: 15)
Show Platforms: Toggle platform level display (default: enabled)
Platform Extension: Bars to extend platforms (default: 7)
Originality Statement
This indicator is original in its multi-dimensional trend approach. While individual components (Hull MA, SuperTrend, ADX, EMAs) are established concepts, this indicator is justified because:
It combines four distinct trend methodologies into a unified classification system
The five-state trend classification provides clear trend assessment
Prismatic gradient visualization creates intuitive trend intensity display
Counter-trend detection with anti-overlap logic identifies potential reversals
MA alignment analysis measures institutional conviction
Integration of Hull MA smoothness with SuperTrend adaptability creates balanced trend detection
The comprehensive dashboard presents all trend dimensions simultaneously
Disclaimer
This indicator is provided for educational and informational purposes only. It is not financial advice. Trading involves substantial risk of loss. Trend analysis does not guarantee profitable trades. Past trends do not guarantee future trends. Always use proper risk management and never risk more than you can afford to lose.
-Made with passion by officialjackofalltrades インジケーター
Velocity Spectrum Analyzer [JOAT]Velocity Spectrum Analyzer
Introduction
The Velocity Spectrum Analyzer is an advanced open-source momentum wave system that combines Munich Wave methodology with ALMA enhancement and multi-basis momentum tracking. This indicator analyzes momentum across five distinct velocity layers, creating a spectrum of momentum waves that reveal trend strength, regime shifts, and momentum alignment across multiple timeframes.
Unlike single-line momentum indicators, the Velocity Spectrum Analyzer provides multi-dimensional momentum analysis through layered EMA calculations, ALMA enhancement, regime classification, and spread analysis. The indicator is designed for traders who understand that momentum flows in waves and that multi-layer alignment signals institutional conviction.
Why This Indicator Exists
This indicator addresses the need for multi-dimensional momentum analysis. By combining five momentum layers with ALMA enhancement and regime detection, it reveals:
Five Velocity Layers: Fast (9), Medium (21), Slow (55), Very Slow (100), and Ultra Slow (200) EMAs create a momentum spectrum
ALMA Enhancement: Arnaud Legoux Moving Average provides adaptive smoothing with reduced lag
Basis Calculations: Averages between EMA layers create intermediate momentum levels
Regime Classification: Extreme Bull/Bear detection using Bollinger-style bands
Spread Analysis: Distance between fast and slow layers measures momentum strength
Wave State Detection: All layers bullish or bearish signals strong directional momentum
Background Coloring: Visual regime indication shows extreme conditions
Core Components Explained
1. Core Momentum Calculation
The indicator starts with basic momentum (current close minus close N bars ago), then applies ALMA for adaptive smoothing:
The ALMA offset (default 0.85) and sigma (default 6) parameters control the balance between responsiveness and smoothness. Higher offset values shift the average toward recent prices, while higher sigma values increase smoothness.
2. Five EMA Layers
Five EMAs are calculated on the momentum values:
Fast EMA (9): Captures short-term momentum shifts
Medium EMA (21): Tracks intermediate momentum trends
Slow EMA (55): Identifies primary momentum direction
Very Slow EMA (100): Reveals long-term momentum bias
Ultra Slow EMA (200): Shows institutional momentum positioning
Each layer responds at different speeds, creating a spectrum of momentum perspectives.
3. Basis Calculations
Five basis levels are calculated as averages between EMA layers:
Basis 1: Average of Fast and Medium EMAs
Basis 2: Average of Medium and Slow EMAs
Basis 3: Average of Slow and Very Slow EMAs
Basis 4: Average of Very Slow and Ultra Slow EMAs
Basis 5: Average of Ultra Slow and Fast EMAs (wraps around)
These basis levels create intermediate momentum zones that smooth transitions between layers.
4. Trend Classification Functions
Two functions classify momentum direction:
Growing: Momentum > basis (bullish momentum)
Falling: Momentum <= basis AND momentum <= ALMA (bearish momentum)
Each basis is classified independently, creating five separate momentum assessments.
5. Regime Detection with Bollinger-Style Bands
The indicator calculates bands around the average of all five basis levels:
Origin: SMA of basis average (default 25 periods)
Deviation: Standard deviation multiplied by factor (default 6.0)
Top Band: Origin + deviation (extreme bullish threshold)
Bottom Band: Origin - deviation (extreme bearish threshold)
When basis 1 and ALMA both exceed the top band with rising momentum, the indicator signals extreme bullish conditions. When both fall below the bottom band with falling momentum, it signals extreme bearish conditions.
6. Mean Range Calculation
A long-term mean range (default 415 bars) tracks the highest and lowest basis average values. The center of this range serves as a reference point for ALMA positioning. When ALMA is above the center mean with all layers bullish, strong upward momentum is confirmed.
7. Wave State Analysis
The indicator tracks when all five basis levels are simultaneously bullish or bearish:
All Bullish: All five basis levels show growing momentum - strong uptrend
All Bearish: All five basis levels show falling momentum - strong downtrend
Mixed: Some layers bullish, some bearish - transitional or choppy conditions
Wave state alignment indicates institutional conviction across all momentum timeframes.
8. Spread Calculation
The spread between Basis 1 (fastest) and Basis 5 (slowest) measures momentum divergence:
Positive Spread (> 10): Fast momentum exceeds slow momentum - bullish acceleration
Negative Spread (< -10): Fast momentum below slow momentum - bearish acceleration
Extreme Spread (> 20 or < -20): Very strong momentum divergence - potential exhaustion
Large spreads indicate strong directional momentum, while narrowing spreads warn of momentum loss.
Visual Elements
Five Velocity Layer Lines: Thick colored lines showing each basis level with dynamic coloring (cyan = bullish, yellow = bearish, white = neutral)
ALMA Enhanced Line: Separate line showing ALMA-adjusted momentum with tri-color scheme
Wave State Line: Zero line colored based on overall wave state
Background Regime: Red background for extreme bull, green background for extreme bear
Information Dashboard: Displays wave state, regime, spread, ALMA position, momentum value, layer alignment, and signal status
Signal Generation
The indicator generates four types of signals:
Lean Short: Bearish crossover with falling Basis 1 and 2, spread <= -10
Maybe Buy: Bearish crossover with falling Basis 1 and 2, extreme bear regime, spread <= -20 (oversold)
Lean Long: Bullish crossover with growing Basis 1 and 2, spread >= 10
Maybe Sell: Bullish crossover with growing Basis 1 and 2, extreme bull regime, spread >= 20 (overbought)
Additional signals:
All Aqua: All layers bullish for 4+ consecutive bars - strong uptrend confirmation
All Yellow: All layers bearish for 4+ consecutive bars - strong downtrend confirmation
How to Use This Indicator
Step 1: Check Wave State
Monitor the dashboard for wave state (All Bullish, All Bearish, or Mixed). Trade in the direction of wave state alignment.
Step 2: Analyze Regime
Watch for extreme bull/bear regimes (red/green backgrounds). These often precede reversals or strong continuation moves.
Step 3: Monitor Spread
Large spreads (> 20 or < -20) indicate strong momentum but potential exhaustion. Narrowing spreads warn of momentum loss.
Step 4: Check ALMA Position
ALMA above center mean with bullish layers confirms uptrend. ALMA below center mean with bearish layers confirms downtrend.
Step 5: Count Layer Alignment
The dashboard shows how many layers are bullish (X/5). 5/5 bullish = strongest uptrend, 0/5 bullish = strongest downtrend.
Step 6: Wait for Signal Confirmation
Lean Long/Short signals work best when wave state aligns. Maybe Buy/Sell signals at extremes offer reversal opportunities.
Best Practices
Trade with wave state alignment, not against it
Use extreme regimes as reversal warnings, not continuation signals
Monitor spread for momentum strength - large spreads indicate strong trends
Wait for all layers to align (5/5) before taking aggressive positions
Use Maybe Buy/Sell signals only at extreme regimes with high spread
Combine with price action - momentum shows intent, price shows result
Be cautious when layers are mixed (2/5 or 3/5) - indicates choppy conditions
Watch for spread narrowing as early warning of trend exhaustion
Input Parameters
Momentum Engine:
Source: Price input (default: close)
Momentum Length: Period for momentum calculation (default: 21)
ALMA Offset: Offset parameter for ALMA (default: 0.85)
ALMA Sigma: Sigma parameter for ALMA (default: 6)
Momentum Layers:
Fast EMA: Short-term momentum (default: 9)
Medium EMA: Intermediate momentum (default: 21)
Slow EMA: Primary momentum (default: 55)
Very Slow EMA: Long-term momentum (default: 100)
Ultra Slow EMA: Institutional momentum (default: 200)
Regime Classification:
Mean Lookback: Period for mean range (default: 415)
StdDev Length: Period for standard deviation (default: 25)
StdDev Multiplier: Band width multiplier (default: 6.0)
Background Offset: Shift background display (default: 0)
Visual Configuration:
Bullish Color: Color for bullish momentum (default: cyan)
Bearish Color: Color for bearish momentum (default: yellow)
Neutral Color: Color for neutral momentum (default: white)
Enable Alerts: Toggle alert conditions (default: enabled)
Originality Statement
This indicator is original in its multi-layer momentum approach. While individual components (EMAs, ALMA, momentum) are established concepts, this indicator is justified because:
It combines five distinct momentum layers into a unified spectrum analysis
The basis calculation system creates intermediate momentum zones between layers
ALMA enhancement provides adaptive smoothing with reduced lag
Regime detection using Bollinger-style bands on basis average identifies extremes
Wave state analysis tracks alignment across all five layers simultaneously
Spread calculation measures momentum divergence between fast and slow layers
The comprehensive dashboard presents all momentum dimensions simultaneously
Disclaimer
This indicator is provided for educational and informational purposes only. It is not financial advice. Trading involves substantial risk of loss. Momentum analysis does not guarantee profitable trades. Past momentum patterns do not guarantee future results. Always use proper risk management and never risk more than you can afford to lose.
-Made with passion by officialjackofalltrades インジケーター
Lattice Trend Helix [JOAT]Lattice Trend Helix
Introduction
The Lattice Trend Helix is an open-source trend analysis indicator built in Pine Script v6. It combines a GMMA-inspired multi-EMA fan system (19 exponential moving averages across fast and slow groups) with a pivot-center SuperTrend, RSI momentum confirmation, and a comprehensive trend strength scoring system. The indicator detects EMA fan alignment, measures trend strength on a 0-100 scale, identifies fan expansion/contraction dynamics, and generates priority-ranked signals including full confluence locks, fan crosses, SuperTrend flips, EMA 200 reclaims, fan burst breakouts, SuperTrend bounces, and displacement impulses.
The Guppy Multiple Moving Average (GMMA) concept, originally developed by Daryl Guppy, uses two groups of EMAs to visualize the behavior of short-term traders (fast group) and long-term investors (slow group). When both groups are aligned and separated, a strong trend is in place. When they converge and cross, a trend change is developing. This indicator extends the GMMA concept by adding a pivot-based SuperTrend for dynamic support/resistance, RSI filtering for momentum confirmation, and a quantified scoring system that turns visual alignment into a measurable number.
Why This Indicator Exists
Single moving average crossover systems are prone to whipsaws. Even dual-MA systems produce frequent false signals in choppy markets. The GMMA approach solves this by requiring alignment across many EMAs simultaneously — a much higher bar than a simple crossover. This indicator takes that concept further:
19-EMA Fan System: 11 fast EMAs (periods 3 through 23) capture short-term trader sentiment. 8 slow EMAs (periods 25 through 60) capture longer-term investor positioning. Full alignment of all 11 fast EMAs in order is a strong signal that short-term traders agree on direction. Full alignment of all 8 slow EMAs confirms institutional agreement.
Pivot-Center SuperTrend: Unlike standard SuperTrend which uses HL2 as the center, this implementation uses a weighted average of detected pivot points. Each new pivot high or low updates the center using the formula: center = (center * 2 + pivot) / 3. This creates a more responsive center line that adapts to actual market structure rather than simple bar midpoints. ATR-based bands around this center define the trend direction.
Trend Strength Score (0-100): Quantifies trend strength from three components — fast EMA alignment (50 points), slow EMA alignment (30 points), and price position relative to EMA 200 (20 points). A score of 100 means all 19 EMAs are perfectly aligned and price is on the correct side of the 200 EMA.
Fan Spread Dynamics: The distance between the fastest EMA (3) and slowest fast EMA (23), normalized by ATR, measures how "open" the fan is. An expanding fan indicates strengthening trend momentum. A contracting fan warns of potential trend exhaustion or reversal.
RSI Momentum Filter: RSI must agree with the fan direction for the highest-confidence signals. This prevents false confluence signals during momentum divergences.
EMA 200 Macro Filter: Price must be above the 200 EMA for confirmed bullish signals and below for confirmed bearish signals, ensuring alignment with the macro trend.
How the EMA Fan Alignment Works
The fast fan consists of 11 EMAs at periods 3, 5, 7, 9, 11, 13, 15, 17, 19, 21, and 23. For bullish alignment, every EMA must be above the next longer one:
// Full fast fan bull alignment requires ALL 10 pairs in order
bool fastBull = ef3 > ef5 and ef5 > ef7 and ef7 > ef9 and ef9 > ef11
and ef11 > ef13 and ef13 > ef15 and ef15 > ef17
and ef17 > ef19 and ef19 > ef21 and ef21 > ef23
This is an extremely high bar. In choppy markets, the fast EMAs will be tangled and neither fastBull nor fastBear will be true. Only in genuine trending conditions do all 11 EMAs sort into perfect order. The same logic applies to the 8 slow EMAs.
The indicator counts how many adjacent pairs are aligned (0-10 for fast, 0-7 for slow) to produce a granular alignment score even when full alignment is not achieved. This allows the trend strength score to reflect partial alignment — a market with 8/10 fast pairs aligned is stronger than one with 4/10, even though neither achieves full alignment.
Pivot-Center SuperTrend
The SuperTrend component uses a unique center calculation based on detected pivot points:
Pivot highs and lows are detected using ta.pivothigh() and ta.pivotlow() with a configurable period
Each new pivot updates the center line using an exponentially weighted formula that gives 2/3 weight to the existing center and 1/3 to the new pivot
Upper and lower bands are calculated as center +/- (ATR Factor * ATR)
Trend direction flips when price crosses the opposite band
The trailing stop ratchets in the trend direction — it can only move favorably, never against the trend
This pivot-based center produces a SuperTrend that is more responsive to actual market structure than the standard HL2-based version. It adapts to the rhythm of the market's swing points rather than just the midpoint of each bar.
Signal Priority System
The indicator generates 8 types of signals, ranked by priority with cooldown-based anti-overlap:
P1 — HELIX LOCK (highest): Full fan alignment (fast + slow) + RSI confirmation + price above/below EMA 200. This is the maximum confluence signal — every factor agrees. A highlight box is drawn around the signal candle.
P2 — LATTICE SYNC: Full fan alignment (fast + slow) without RSI/EMA200 confirmation. Strong but not maximum confluence.
P3 — TREND FLIP: SuperTrend direction change. The pivot-center SuperTrend has flipped from bearish to bullish or vice versa.
P4 — FAN CROSS: The fast fan median (EMA 13) crosses the slow fan median (EMA 40). This is the GMMA equivalent of a moving average crossover, but using the center of each fan group.
P5 — MACRO CROSS: Price crosses the EMA 200 — a major structural event that changes the macro trend context.
P6 — FAN BURST: The fan spread transitions from contracting to expanding while the trend score is above 50. This indicates a breakout from compression — similar to a Bollinger squeeze release but measured through EMA dynamics.
P7 — ST BOUNCE: Price touches the SuperTrend line and bounces in the trend direction. This is a pullback-to-support/resistance signal unique to this indicator. A separate 5-bar cooldown prevents repeated bounce signals during extended touches.
P8 — IMPULSE (lowest): Displacement candle detection — large body (>70% of range, >2x average body). These indicate aggressive institutional order flow.
Trend Strength Score Breakdown
The 0-100 score is computed from three weighted components:
Fast EMA Alignment (50 points): The number of aligned adjacent pairs (max 10) divided by 10, multiplied by 50. Full fast alignment = 50 points. Half alignment = 25 points.
Slow EMA Alignment (30 points): The number of aligned adjacent pairs (max 7) divided by 7, multiplied by 30. Full slow alignment = 30 points.
EMA 200 Filter (20 points): If price is above EMA 200 and the fast fan leans bullish, or below EMA 200 and the fast fan leans bearish, 20 points are added. This rewards macro-aligned trends.
The score is displayed in the HUD with both a number and a visual bar (||||......). Scores above 70 indicate strong, tradeable trends. Scores between 40-70 indicate developing or weakening trends. Below 40 indicates choppy or transitional conditions.
Visual Design
The indicator uses a "Cyberpunk" color theme — electric cyan, hot magenta, neon yellow, deep violet, and chrome accents:
Fast EMA Fan: All 11 lines in a single color that adapts to alignment — cyan for bullish, magenta for bearish, steel grey for neutral. Configurable opacity.
Slow EMA Fan: All 8 lines in deeper tones — teal for bullish, violet for bearish, steel grey for neutral.
EMA 200: Three-layer neon glow effect (outer glow, mid glow, core line) that shifts between cyan (above) and violet (below).
Holographic Ribbon: Fill between the fastest (EMA 3) and slowest (EMA 23) fast EMAs, creating a ribbon that expands with trend strength and contracts during consolidation.
SuperTrend: Four-layer neon glow step-line (88%, 72%, 50%, 10% transparency) in cyan (bullish) or magenta (bearish).
Regime Background: Subtle background tinting for confirmed bull (cyan) or confirmed bear (magenta) conditions.
Candle Coloring: Multi-tier coloring based on confirmation level — confirmed bull/bear, strong bull/bear, weak bull/bear, or neutral.
HUD Dashboard
The HUD displays 14 metrics:
Trend direction (Bullish/Bearish/Neutral)
Strength score with visual bar (||||......)
Fan state (Strong Bull/Bear, Weak Bull/Bear, Converging)
SuperTrend direction
EMA 200 position (Above/Below)
Alignment counts (Fast: X/10, Slow: X/7)
Fan Spread value with state (Expanding/Contracting/Stable)
RSI value with bull/bear/neutral classification
Confluence count (0-5): fast alignment + slow alignment + SuperTrend agreement + RSI agreement + EMA 200 agreement
SuperTrend distance from price
Volume ratio (current vs 20-bar average)
Confirmed signal status (CONFIRMED BULL/BEAR or ---)
Input Parameters
EMA Fan:
Show Fast/Slow EMAs: Toggle each fan group
Show EMA 200: Toggle macro filter line
Fast/Slow EMA Opacity: Control transparency of each fan group
SuperTrend:
Show SuperTrend: Toggle the pivot-center SuperTrend
Pivot Period: Lookback for pivot detection (default: 3)
ATR Factor: Band width multiplier (default: 2.5)
ATR Length: Period for ATR calculation (default: 14)
Visual:
Show Trend Ribbon: Toggle holographic ribbon fill
Show Fan Crosses: Toggle fan cross signals
Show Regime Background: Toggle background tinting
SuperTrend Neon Glow: Toggle 4-layer glow effect
Color Candles: Toggle multi-tier candle coloring
HUD Panel: Toggle dashboard
Momentum Filter:
Show RSI Confirmation: Toggle RSI requirement for confirmed signals
RSI Length: Period (default: 14)
RSI Bull/Bear Threshold: Directional thresholds (default: 55/45)
How to Use This Indicator
Step 1: Check Fan Alignment
Look at the fan state in the HUD. "Strong Bull" or "Strong Bear" means both fast and slow fans are fully aligned — the strongest trend condition. "Weak" means only the fast fan is aligned — a developing or weakening trend.
Step 2: Verify with SuperTrend
The SuperTrend should agree with the fan direction. Fan bullish + SuperTrend bullish = high conviction. Disagreement suggests a transitional market.
Step 3: Check the Strength Score
Scores above 70 are strong trends. Use the visual bar for quick assessment. The confluence count (0-5) tells you how many independent factors agree.
Step 4: Trade the Signals
HELIX LOCK is the highest-conviction entry — all factors agree. LATTICE SYNC and TREND FLIP are strong. FAN CROSS and MACRO CROSS are structural. ST BOUNCE provides pullback entries within established trends.
Step 5: Monitor Fan Spread
Expanding fan = strengthening trend. Contracting fan = weakening trend or approaching reversal. FAN BURST signals mark the transition from contraction to expansion.
Best Practices
The 19-EMA fan is most effective on timeframes of 5 minutes and above. Very low timeframes produce too much noise for meaningful alignment.
Full fan alignment is rare and powerful. Do not expect it on every trade — it represents the highest-conviction conditions.
The SuperTrend bounce signal works best in established trends. In choppy markets, bounces may fail.
Fan crosses (fast median vs slow median) are the GMMA equivalent of MA crossovers — they confirm trend changes but lag the actual turn.
The EMA 200 filter is a macro-level gate. Ignoring it means trading against the larger trend, which reduces probability.
Use the fan spread dynamics to time entries — entering when the fan is expanding gives you momentum. Entering when it is contracting means you are fighting exhaustion.
The confluence count (0-5) is a quick decision filter. 4-5 = high conviction. 2-3 = moderate. 0-1 = low conviction.
Limitations
EMAs are lagging indicators. Full fan alignment is confirmed after the trend has already started, not at the exact turn.
The 19-EMA system uses significant computational resources. On very long charts with many bars, loading may be slower.
Pivot-center SuperTrend depends on pivot detection, which has an inherent delay equal to the pivot period.
Fan alignment can persist in overextended trends. Full alignment does not mean the trend will continue indefinitely.
The RSI filter can occasionally prevent valid signals during strong momentum divergences.
The indicator is optimized for trending markets. In range-bound conditions, the fan will be tangled and few signals will fire — which is by design.
EMA periods are fixed (3-23 fast, 25-60 slow). Different instruments or timeframes might benefit from different period sets, but the GMMA standard periods are well-tested across markets.
Technical Implementation
Built with Pine Script v6 using:
19 EMA calculations at global scope (11 fast + 8 slow) for Pine v6 compliance
Pivot-based SuperTrend center with exponentially weighted pivot averaging
Granular alignment counting (0-10 fast, 0-7 slow) for trend strength scoring
Fan spread normalization by ATR for cross-instrument comparability
8-tier priority signal system with cooldown-based anti-overlap
Separate cooldown tracking for SuperTrend bounce signals
4-layer neon glow rendering for SuperTrend and EMA 200
Holographic ribbon fill between fan extremes
Multi-tier candle coloring based on confirmation level
barstate.isconfirmed gating on all signal generation
9 alert conditions covering alignment changes, fan crosses, SuperTrend flips, confirmed signals, and fan expansion
Originality Statement
This indicator is original in its synthesis of the GMMA fan concept with pivot-center SuperTrend and quantified trend scoring. While GMMA and SuperTrend are established concepts, this indicator is justified because:
The pivot-center SuperTrend uses a weighted average of actual market pivots rather than simple HL2, creating a more structurally responsive trend line
The trend strength score (0-100) quantifies fan alignment into a single actionable metric with three weighted components
Fan spread dynamics (expansion/contraction tracking normalized by ATR) provide momentum acceleration/deceleration information not available in standard GMMA implementations
The 8-tier priority signal system with separate cooldown tracking for SuperTrend bounces prevents visual clutter while capturing all significant events
RSI momentum filtering and EMA 200 macro gating create a multi-layer confirmation framework that reduces false signals
The confluence count (0-5) provides an instant assessment of how many independent factors agree
The Cyberpunk theme with 4-layer neon glow and holographic ribbon creates a distinctive visual identity where trend strength is immediately apparent from the fan's visual character
Disclaimer
This indicator is provided for educational and informational purposes only. It is not financial advice or a recommendation to buy or sell any financial instrument. Moving average systems identify trends after they have started — they do not predict trend changes in advance. Full fan alignment can occur in overextended trends that are about to reverse. SuperTrend bounces can fail. Past alignment patterns do not guarantee future trend behavior. Always use proper risk management and never risk more than you can afford to lose. The author is not responsible for any losses incurred from using this indicator.
-Made with passion by officialjackofalltrades
インジケーター
Alpha Signal Engine [MarkitTick]💡 The Alpha Signal Engine is an advanced, multi-dimensional trend-following system designed to provide traders with highly filtered, high-probability market signals. At its core, it dynamically calculates a volatility-adjusted trailing band to determine the primary market direction. However, unlike traditional trend indicators that rely on a single data point, this engine passes every potential trend reversal through a rigorous, six-layer filtering mechanism. By requiring confluence across higher timeframe trends, momentum, volume, volatility regimes, and price action strength, it drastically reduces the noise and false signals inherent in choppy markets. It also features a built-in heads-up dashboard and fully formatted JSON webhook capabilities for automated trading integration.
✨ Originality and Utility
● A Dynamic, Adaptive Baseline
Standard trailing stop or trend indicators, such as the classic Supertrend, typically use a static multiplier against the Average True Range (ATR). The Alpha Signal Engine innovates by introducing a "Dynamic Factor." This factor continuously adapts the band's distance from price by factoring in the current baseline multiplier, the relative volatility (ATR normalized by price), and the immediate price change momentum. This allows the bands to tighten during periods of strong, directional momentum and widen during erratic volatility, providing a more responsive and intelligent trailing mechanism.
● The Six-Pillar Filtering Gateway
The true utility of this indicator lies in its modular filtering engine. Traders often have to clutter their charts with half a dozen indicators to confirm a setup. This script centralizes that logic. Users can selectively enable or disable filters based on their specific asset and trading style, turning the indicator into a customizable algorithmic engine. Whether you need volume confirmation, ADX trend strength, or simple RSI momentum, the script handles the complex boolean logic internally and only outputs a signal when your precise market conditions are met.
🔬 Methodology and Concepts
● Dynamic Factor Calculation
The indicator establishes its baseline trend using an upper and lower band. The distance of these bands from the median price is dictated by a dynamically calculated factor. This factor is the sum of a base value, a volatility component (ATR divided by Close, scaled by a user weight), and a price movement component (percentage change of the close, scaled by a user weight). This raw factor is then smoothed using a Simple Moving Average (SMA) to prevent erratic band shifts.
● Trend Determination
The trend direction flips when the closing price crosses the active dynamic band. If the price closes above the upper band, the trend shifts bullish, and the lower band becomes the active support. Conversely, closing below the lower band shifts the trend bearish, making the upper band the active resistance.
● The Filter Matrix
A signal is only generated when a trend flip aligns with all activated filters:
HTF Alignment: Uses the request context to pull the trend direction from a higher timeframe, ensuring you are not trading against the macro trend.
ADX Trending: Measures the Average Directional Index to ensure the market is in an active trending phase (above a defined threshold) rather than a sideways chop.
Volume Surge: Compares current volume against a Volume SMA. The current bar must exhibit a volume spike greater than the defined multiplier to confirm institutional participation.
RSI Momentum: A simple but effective gatekeeper requiring the Relative Strength Index to be above 50 for longs and below 50 for shorts.
ATR Volatility Regime: Compares the current ATR against a 50-period SMA of the ATR. It ensures the market is operating within a "normal" volatility ratio, preventing entries during extreme, unpredictable volatility spikes or dead, illiquid periods.
Candle Body Strength: Calculates the absolute size of the candle body (Open to Close) and mandates it must be larger than a specific fraction of the ATR, ensuring the signal candle has true directional conviction.
🎨 Visual Guide
● Chart Elements
Up Trend Line: Displayed as a solid, teal-colored line trailing below the price action during a bullish phase. It acts as dynamic support.
Down Trend Line: Displayed as a solid, bright pink/red line trailing above the price action during a bearish phase. It acts as dynamic resistance.
Trend Cloud (Fill): A colored gradient fill exists between the median price and the active trend line. A teal cloud visually represents bullish dominance, while a pink/red cloud represents bearish dominance.
Buy Signals: Indicated by small, teal "B" labels positioned below the signal candle.
Sell Signals: Indicated by small, pink/red "S" labels positioned above the signal candle.
● Filter Dashboard
Located in the top right corner of the chart, this HUD (Heads-Up Display) provides a real-time status check of your system.
The left column lists the available filters (HTF Align, ADX Trend, Vol Surge, RSI Gate, ATR Regime, Body Str).
The right column displays the current status of each filter.
A gray "OFF" indicator means the user has disabled the filter in the settings.
A green "ON" or "Aligned" text indicates the condition is currently met.
A red "Opposed" or unlit indicator means the condition is active but currently failing to meet the required criteria.
The bottom rows clearly state the current overarching trend direction and whether a signal is pending or waiting.
📖 How to Use
• Interpreting the System
To effectively use the Alpha Signal Engine, begin by observing the main trend lines and the color of the cloud. This provides your baseline bias. Do not take trades purely on the band flipping. Instead, rely on the explicit "B" and "S" labels.
• Signal Execution
When a "B" (Buy) or "S" (Sell) label appears, it means the price has successfully flipped the trend AND all user-activated filters in the dashboard are glowing green. This is your entry trigger. The active trend line (the teal line for longs, the pink line for shorts) serves as an ideal, dynamic stop-loss placement.
• Customizing the Engine
The system is designed to be tuned. If you are trading a highly liquid asset like major forex pairs, you may want to enable the ADX and HTF filters to catch long, sustained moves. If you are trading volatile crypto assets, enabling the Volume Surge and Candle Body filters can help you avoid fake-outs and trap wicks. Monitor the on-chart dashboard to see which filters are keeping you out of bad trades and adjust your settings accordingly.
⚙️ Inputs and Settings
• Supertrend Settings
ATR Length: The lookback period for calculating the Average True Range.
Base Factor: The starting multiplier for the dynamic bands.
Volatility & Price Change Weights: Determines how aggressively the bands react to sudden spikes in relative volatility and price momentum.
Factor Smoothing: Applies an SMA to the final dynamic multiplier to keep the bands stable.
• Filter Settings
Enable HTF Alignment: Toggle and define the higher timeframe (e.g., Daily) to align with.
ADX Settings: Toggle the filter, define the lookback length, and set the minimum trend strength threshold (default is 20).
Volume Settings: Toggle the filter, define the Volume MA length, and set the multiplier required to classify as a "surge."
RSI Settings: Toggle the filter and set the RSI lookback length.
ATR Regime Settings: Define the minimum and maximum acceptable ratios of current ATR versus historical ATR.
Candle Body Settings: Define the minimum required size of the candle body as a fraction of the current ATR.
• Webhook Action Names
These text inputs allow you to define specific payload strings (e.g., "long", "closeshort") that the indicator will output via JSON alerts, perfectly formatting the data for third-party automation services like 3Commas or PineConnector.
🔍 Deconstruction of the Underlying Scientific and Academic Framework
The Alpha Signal Engine is grounded in several well-documented tenets of quantitative financial analysis and statistical market theory.
● Volatility-Adjusted Trailing Stops
The foundation of the indicator relies on the Average True Range (ATR), introduced by J. Welles Wilder Jr. The ATR is a measure of the degree of price volatility. By tying the trailing stop (the dynamic band) to the ATR, the system acknowledges the statistical reality of market variance. The innovation here is the dynamic multiplier. By adjusting the distance based on the normalized rate of change (momentum), the script attempts to solve the lagging nature of fixed-multiplier trailing stops, utilizing principles found in adaptive moving averages (like Kaufman's AMA), where sensitivity increases alongside directional conviction.
● Multi-Dimensional Confluence Theory
The filtering engine operates on the academic principle of conditional probability and confluence. In market microstructure, no single indicator holds a permanent statistical edge.
The HTF filter is rooted in Dow Theory, prioritizing the primary trend over secondary reactions.
The ADX filter utilizes Wilder's Directional Movement Index to mathematically separate trending environments from mean-reverting environments, applying a statistical threshold to directional strength.
The Volume Surge filter relies on the Volume Price Trend concepts, positing that significant price movements must be sponsored by outsized volume to validate institutional participation and avoid anomalous low-liquidity spikes.
The ATR Regime filter applies mean-reverting principles to volatility itself (volatility clustering), ensuring that entries are only taken when the variance of the asset is within historically "normal" parameters, avoiding the fat tails of extreme market shocks.
By chaining these disparate mathematical models (trend, momentum, volume, volatility) via Boolean logic, the system mathematically reduces the frequency of trades while theoretically increasing the probability of the remaining sample size.
⚠️ Disclaimer
All provided scripts and indicators are strictly for educational exploration and must not be interpreted as financial advice or a recommendation to execute trades. I expressly disclaim all liability for any financial losses or damages that may result, directly or indirectly, from the reliance on or application of these tools. Market participation carries inherent risk where past performance never guarantees future returns, leaving all investment decisions and due diligence solely at your own discretion. インジケーター
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MTF Bias Dashboard (TOTAL STRENGTH)📊 Multi-Timeframe Bias Dashboard (Total Strength)
This indicator gives a clear, no-noise view of market direction by analyzing multiple timeframes and combining them into a single actionable bias.
It tracks the relationship between price and the 200 EMA across key timeframes (15M, 30M, 1H, 4H) to determine whether the market is bullish or bearish, while also measuring the strength of each trend.
🔍 What It Shows
Directional Bias (Bullish / Bearish) for each timeframe
Trend Strength (0–100) based on distance from the 200 EMA
A Total Strength Score that combines all timeframes into one number
This gives you both:
The bigger picture trend
The immediate trading environment
⚡ How It Works
Each timeframe contributes to an overall score:
Bullish trends add positive strength
Bearish trends add negative strength
These values are combined into a Net Strength reading, which tells you who’s in control of the market.
🧠 How to Read It
Strong Positive Total → Market is bullish → Focus on longs
Strong Negative Total → Market is bearish → Focus on shorts
Near Zero → Market is choppy → Avoid trading
Higher timeframe alignment (1H + 4H) defines the main bias, while lower timeframes (15M + 30M) help time entries.
🎯 Why This Is Useful
Eliminates guesswork and conflicting signals
Keeps you trading with trend, not against it
Helps avoid low-quality trades in choppy markets
Perfect for day traders and prop firm traders
🚀 Best Use Case
Use this as a trend filter + bias confirmation tool, then pair it with your entry model (price action, MACD, liquidity, etc.) for precision entries. インジケーター
Kalman Volume Trend [BigBeluga]🔵 OVERVIEW
Kalman Volume Trend is an advanced trend-following system that combines the predictive power of a Kalman Filter with real-time volume delta analysis. Unlike standard moving averages that suffer from significant lag, the Kalman Filter uses a recursive mathematical algorithm to estimate the "true" trend by filtering out market noise.
The indicator not only identifies directional regimes but also visualizes the intensity of buying and selling pressure directly on the trend line, providing a multi-dimensional view of market conviction.
🔵 CONCEPT
Kalman Filter Logic — A state-space model that predicts price movement and then corrects itself based on new data, resulting in a smoother yet more responsive trend line than traditional EMAs.
Adaptive ATR Bands — The trend direction is determined by price breaking through volatility-adjusted bands, reducing whipsaws in sideways markets.
Volume-Weighted Trend Lines — The indicator plots "Volume Bars" extending from the trend line, where the length and color represent the relative strength of the volume delta.
Cumulative Trend Statistics — It tracks the total buy volume, sell volume, and net delta from the exact moment a new trend begins.
🔵 HOW IT WORKS (IN-DEPTH)
1️⃣ The Kalman Filtering Process
The script utilizes two primary parameters: Process Noise (Q) and Measurement Noise (R) .
It calculates a "State Estimate" (the trend) by balancing its previous prediction against the current price.
If the price is "jittery" (high R), the filter smooths the line; if the trend is moving decisively (low Q), it tracks the price more aggressively.
2️⃣ Trend Direction & Volatility Bands
Two bands are projected around the Kalman line based on a multiplier of the Average True Range (ATR) .
A Bullish trend is triggered when price closes above the upper band.
A Bearish trend is triggered when price closes below the lower band.
Once a trend is established, the opposite band acts as the trailing "Trend Line" to provide a clear buffer for price fluctuations.
3️⃣ Volume Delta Visualization
Small vertical candles ("Volume Bars") are plotted along the trend line.
These bars represent the Normalized Volume Delta (Close vs. Open and Volume intensity).
Large bars indicate high-conviction participation, while small bars suggest waning interest or consolidation.
4️⃣ Extreme Volume & Cumulative Dashboard
When volume exceeds 1.5x its recent average, an "X" label appears on the chart to mark an Exhaustion or Ignition point.
A bottom-right dashboard displays a vertical histogram showing the balance of power (BUY vs. SELL vs. DELTA) for the current trend only .
🔵 KEY FEATURES
Recursive Kalman Algorithm: High-accuracy trend tracking with minimal lag.
Integrated Volume Profiling: See volume delta without needing a separate sub-window.
Dynamic Trend Dashboard: Automatically resets at every trend flip to show fresh volume stats.
Volatility-Aware: Uses 200-period ATR to ensure bands adapt to changing market conditions.
Volume Extreme Alerts: Identifies high-volume spikes that often precede trend reversals.
🔵 DASHBOARD METRICS
BUY — Total volume accumulated on bullish candles since the trend started.
SELL — Total volume accumulated on bearish candles since the trend started.
DELTA — The net difference between buying and selling pressure.
TOTAL VOLUME — The total "fuel" spent during the current directional regime.
🔵 HOW TO USE
Riding the Trend: Stay in the trade as long as the Kalman line color remains consistent.
Spotting Weakness: If the Kalman line is Bullish (Blue) but the Volume Bars are consistently negative or shrinking, the trend may be losing steam.
High-Volume Breakouts: Look for the "X" labels at the start of a trend shift; this confirms institutional participation in the new direction.
Dashboard Confirmation: Use the vertical histogram to confirm if the buyers or sellers are truly in control during a pullback to the trend line.
🔵 CONCLUSION
Kalman Volume Trend offers a sophisticated approach to trend analysis by merging high-level signal processing with raw volume data. By focusing on "clean" price data and weighting it with volume delta, it helps traders filter out market noise and focus on high-conviction movements. インジケーター
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Trend Resonance Oscillator [JOAT]Trend Resonance Oscillator
Introduction
The Trend Resonance Oscillator is an open-source non-overlay indicator that measures multi-timeframe trend alignment and produces a composite resonance score. It fetches trend data from up to five configurable timeframes, calculates whether they agree on direction, and outputs an oscillator that reflects the degree of alignment. When most or all timeframes point the same way, the oscillator reaches extreme values and the indicator declares a state of "resonance" — a condition where directional conviction is high across the time spectrum. It also includes quantum-inspired coherence scoring, harmonic pattern detection, and momentum alignment visualization.
Built with Pine Script v6, the indicator uses custom types for trend state, resonance state, timeframe data, quantum state, and harmonic patterns.
Why This Indicator Exists
A trade taken in the direction of the 5-minute trend may fail if the 1-hour and daily trends disagree. Multi-timeframe alignment is one of the most reliable filters for trade quality, but checking multiple timeframes manually is tedious and subjective. This indicator automates that process by:
Simultaneous MTF analysis: Fetches close, EMA, and rate-of-change data from five configurable timeframes in a single indicator
Alignment scoring: Quantifies how many timeframes agree on direction and how strong each trend is, producing a single composite score
Resonance detection: Identifies periods when alignment exceeds a configurable threshold, signaling high-conviction directional conditions
Confluence signals: Generates labeled signals when a minimum number of timeframes align, providing clear entry confirmation
Coherence and entanglement metrics: Measures the consistency and correlation between timeframe trends, adding depth beyond simple directional agreement
Core Components Explained
1. Multi-Timeframe Trend Detection
For each of the five timeframes (default: 5m, 15m, 1H, 4H, Daily), the indicator fetches close price, EMA, and rate-of-change using `request.security()` with proper lookahead settings to avoid repainting:
float _tf1Close = request.security(syminfo.tickerid, tf1, close, barmerge.gaps_off, barmerge.lookahead_off)
float _tf1EMA = request.security(syminfo.tickerid, tf1, _globalEMA, barmerge.gaps_off, barmerge.lookahead_off)
Each timeframe's trend is classified as bullish, bearish, or flat based on the percentage difference between close and EMA relative to a configurable threshold (default 0.5%). The trend strength is calculated as the magnitude of that percentage difference, capped at 100.
2. Alignment Score Calculation
The alignment score counts how many timeframes are bullish versus bearish, then produces a normalized score from -100 (all bearish) to +100 (all bullish):
+100: All active timeframes are bullish — maximum bullish alignment
+60: Majority bullish with some neutral — strong bullish bias
0: Equal bullish and bearish — no directional consensus
-60: Majority bearish — strong bearish bias
-100: All bearish — maximum bearish alignment
The alignment score is weighted by the average trend strength across all active timeframes, so a +80 alignment with strong individual trends produces a higher oscillator value than +80 alignment with weak trends.
3. Resonance Detection
Resonance occurs when the ratio of aligned timeframes to total active timeframes exceeds the resonance threshold (default 0.7) and the aligned count meets the minimum confluence requirement (default 4 timeframes). During resonance, the background is tinted to indicate the directional bias, and a duration counter tracks how long the resonance state has persisted.
Sustained resonance (high duration) suggests a strong, established trend. New resonance (low duration) may signal the beginning of a directional move. The dashboard displays the resonance score, aligned count, and duration for quick assessment.
The Trend Resonance Oscillator panel showing the main oscillator line with gradient coloring, MTF trend bars at the bottom showing individual timeframe directions, resonance background shading during a strong bullish alignment, and confluence/resonance signal labels
4. Quantum Coherence and Entanglement
The indicator calculates two additional metrics inspired by quantum physics concepts (used as analytical metaphors, not literal physics):
Coherence: The ratio of aligned timeframes to total timeframes. A coherence of 1.0 means perfect agreement. When coherence exceeds the threshold (default 0.8), the indicator enters a "coherent" state, which is visualized as a subtle wave pattern on the oscillator.
Entanglement: Measures the pairwise correlation between all timeframe trends. For each pair of timeframes, if they agree on direction, the entanglement score increases; if they disagree, it decreases. High entanglement means timeframes are moving in lockstep.
for i = 0 to 3
for j = i + 1 to 4
if trend_i != 0 and trend_j != 0
correlation = trend_i == trend_j ? 1.0 : -1.0
entanglement += correlation
pairs += 1
When the quantum superposition score (combination of coherence and entanglement) exceeds a threshold, a "quantum collapse" signal fires, indicating that all timeframes have converged to a single directional state.
5. Harmonic Pattern Detection
The harmonic module detects cyclical patterns in the resonance data. When resonance is sustained for more than 10 bars, the pattern is classified as a sine wave (smooth, established trend). When resonance is new or intermittent, it is classified as a square wave (choppy, emerging trend). The harmonic wave is plotted as a subtle overlay on the oscillator.
6. Confluence and Signal System
The indicator generates three tiers of signals, with higher tiers taking priority:
CONF (Confluence): Minimum timeframes aligned with alignment score >= 70
RES (Resonance): Strong resonance with score >= 80
QTM (Quantum): Quantum collapse — all metrics converge to a single state
Each signal fires only on its first bar (not continuously), preventing chart clutter. Signals are color-coded with gradient intensity based on the underlying strength.
Visual Elements
Main Oscillator: Smoothed alignment score plotted as a line with gradient coloring from bearish to bullish
Reference Levels: Lines at 0 (neutral), +/-50 (moderate), +/-80 (strong)
MTF Trend Bars: Five colored column bars at the bottom of the panel, each representing one timeframe's trend direction and strength
Resonance Background: Tinted background during resonance states
Quantum Superposition Line: Step-line showing the quantum composite score
Coherence Wave: Subtle area plot showing coherence oscillation
Harmonic Pattern: Sine/square wave overlay during active resonance
Momentum Alignment: Area histogram showing aggregate momentum across timeframes
Convergence/Divergence: Histogram showing agreement between momentum and oscillator
Signal Labels: CONF, RES, and QTM labels at signal points
Entanglement Lines: Visual connections when timeframe entanglement is high
Dashboard: Comprehensive table showing each timeframe's trend, strength, and the aggregate resonance metrics
Input Parameters
Multi-Timeframe Settings:
Toggle and configure each of 5 timeframes (default: 5m, 15m, 1H, 4H, Daily)
Trend Detection:
Trend EMA Length (default 20), Momentum Length (default 14), Trend Threshold (default 0.5%)
Resonance Settings:
Resonance Lookback (default 20), Resonance Threshold (default 0.7)
Show Resonance Zones toggle
Alignment Scoring:
Min TFs for Confluence (default 4)
Show Alignment Score and Confluence Signals
Advanced Resonance:
Quantum Resonance, Coherence Waves, Entanglement Lines, Harmonic Patterns toggles
Coherence Threshold (default 0.8), Harmonic Period (default 8)
Visual Settings:
Show Oscillator, MTF Bars, Dashboard, Glow Effects, Waveform
Color Scheme: Quantum, Classic, Professional, Neon
How to Use This Indicator
Step 1: Check the MTF trend bars at the bottom of the panel. If all five bars are the same color (all bullish or all bearish), you have strong multi-timeframe alignment.
Step 2: Read the oscillator value. Values above +50 indicate moderate bullish alignment; above +80 indicates strong alignment. The inverse applies for bearish readings.
Step 3: Watch for resonance background shading. When the background turns bullish or bearish, the indicator has detected sustained multi-timeframe agreement — this is the highest-conviction environment for directional trades.
Step 4: Use CONF, RES, and QTM signals as entry confirmations. A CONF signal in the direction of the oscillator provides moderate confirmation. A RES or QTM signal provides strong confirmation.
Step 5: Monitor the momentum alignment area. When momentum and the oscillator agree, the move has both directional alignment and momentum behind it. When they diverge, the move may be losing steam.
Dashboard showing all five timeframes with their individual trend states, the aggregate resonance score, coherence level, entanglement reading, and harmonic pattern status
Indicator Limitations
Multi-timeframe data requires sufficient history on all selected timeframes. On newly listed instruments, higher timeframe data may be limited.
The indicator uses `request.security()` with `barmerge.lookahead_off` to prevent repainting, but the inherent delay of higher timeframe data means signals reflect confirmed (not real-time) higher timeframe states.
Alignment does not guarantee profitable trades. All timeframes can align in one direction and then reverse simultaneously.
The quantum and harmonic features are analytical metaphors that provide useful metrics, not literal physics simulations.
On very low timeframes (1m or less), higher timeframe data updates infrequently, which can make the oscillator appear static for extended periods.
The indicator makes multiple `request.security()` calls, which counts against TradingView's security call limit.
Originality Statement
This indicator is original in its comprehensive multi-timeframe resonance framework. While MTF trend indicators exist, this indicator is justified because:
It produces a quantified resonance score that measures not just direction but the degree and duration of multi-timeframe agreement
The coherence and entanglement metrics add pairwise correlation analysis between timeframes, going beyond simple directional counting
The three-tier signal system (CONF/RES/QTM) provides graduated confidence levels based on the strength of alignment
Harmonic pattern detection on the resonance data identifies whether alignment is sustained (sine) or emerging (square)
The momentum alignment overlay shows whether aggregate momentum across timeframes supports the directional reading
The weighted oscillator combines alignment direction with individual trend strength for a more nuanced composite score
Disclaimer
This indicator is provided for educational and informational purposes only. It is not financial advice or a recommendation to buy or sell any financial instrument. Trading involves substantial risk of loss. Multi-timeframe alignment is a powerful filter but does not guarantee profitable trades. Always use proper risk management. The author is not responsible for any losses incurred from using this indicator.
-Made with passion by officialjackofalltrades
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Signal Qualification Engine [JOAT]Signal Qualification Engine
Introduction
The Signal Qualification Engine is a sophisticated multi-layer signal filtering system designed to identify high-probability trading opportunities through comprehensive confluence analysis. This indicator solves the universal trading problem of signal quality - not all signals are created equal, and distinguishing between mediocre setups and high-probability opportunities is what separates successful traders from the crowd. By evaluating signals across trend, momentum, volume, and structure layers, this engine provides institutional-grade signal qualification that helps traders focus only on the best opportunities.
This tool is built for traders who understand that edge in trading comes from the confluence of multiple factors rather than any single indicator. Whether you're a discretionary trader looking for confirmation, a systematic trader needing signal filtering, or an algorithm developer requiring quality scoring, this engine provides the comprehensive analysis needed to elevate your trading from random signals to systematic, high-quality setups.
Why This Indicator Exists
Most traders struggle with signal overload - too many signals, varying quality, and no systematic way to evaluate them. This indicator addresses that critical problem by:
Multi-Layer Analysis: Evaluates signals across four independent analytical layers
Quality Scoring: Provides objective, numerical quality scores for every signal
Confluence Detection: Identifies when multiple factors align for high-probability setups
Risk/Reward Validation: Ensures signals offer adequate profit potential relative to risk
Premium Signals: Flags exceptional setups with maximum confluence
Visual Zones: Shows entry zones, stop levels, and targets for clear risk management
The engine transforms subjective signal evaluation into an objective, systematic process that can be consistently applied across all market conditions and instruments.
Core Components Explained
1. Trend Analysis Layer
The trend layer evaluates the directional bias using multiple trend indicators:
// Trend scoring
int trend_bull_score = 0
int trend_bear_score = 0
// Moving average analysis
if price_above_fast_ma
trend_bull_score += 1
if price_above_slow_ma
trend_bull_score += 1
if ma_bullish_cross
trend_bull_score += 1
// ADX analysis
if adx > i_adx_thresh
trend_bull_score += plus_di > minus_di ? 2 : 0
trend_bear_score += minus_di > plus_di ? 2 : 0
Trend components:
Price vs MAs: Position relative to fast and slow moving averages
MA Crossovers: Recent trend changes and confirmation
ADX Strength: Trend strength above threshold (default 25)
Directional Movement: +DI vs -DI for trend direction
Trend Score: Cumulative trend strength (0-5 points)
The trend layer ensures we only trade in the direction of the established trend or during trend changes with confirmation.
2. Momentum Analysis Layer
Momentum is evaluated through multiple oscillators to ensure optimal timing:
// Momentum scoring
int momentum_bull_score = 0
int momentum_bear_score = 0
// RSI analysis
if rsi > 50 and rsi < 70 and rsi > rsi
momentum_bull_score += 1
if rsi < 50 and rsi > 30 and rsi < rsi
momentum_bear_score += 1
// Stochastic analysis
if stoch_k > stoch_d and stoch_k < 80
momentum_bull_score += 1
if stoch_k < stoch_d and stoch_k > 20
momentum_bear_score += 1
// MACD analysis
if macd_hist > 0 and macd_hist > macd_hist
momentum_bull_score += 1
if macd_hist < 0 and macd_hist < macd_hist
momentum_bear_score += 1
Momentum components:
RSI Direction: Momentum direction with overbought/oversold filters
Stochastic Crossovers: Entry timing with extreme level avoidance
MACD Histogram: Trend acceleration and deceleration
Momentum Score: Cumulative momentum strength (0-3 points)
Divergence Detection: Price/momentum divergences for early signals
The momentum layer ensures we enter when momentum supports our directional bias.
3. Volume Analysis Layer
Volume confirms the strength and conviction behind price movements:
// Volume analysis
float vol_sma = ta.sma(volume, 20)
float vol_ratio = vol_sma > 0 ? volume / vol_sma : 1.0
bool above_avg_vol = volume > vol_sma * 1.2
bool high_vol_session = session_vol_ratio > 1.5
// Volume scoring
int volume_score = 0
if above_avg_vol
volume_score += 1
if high_vol_session
volume_score += 1
if vol_ratio > 1.5
volume_score += 1
Volume components:
Volume Ratio: Current volume relative to 20-period average
Above Average Volume: Confirms signal strength (20% above average)
Session Volume Analysis: Compares current volume to historical session averages
Volume Score: Cumulative volume confirmation (0-3 points)
Volume Spike Detection: Exceptional volume that may signal institutional activity
The volume layer ensures signals have sufficient participation to be reliable.
4. Structure Analysis Layer
Structure identifies key levels where professional traders place orders:
// Structure analysis
float swing_high = ta.pivothigh(high, i_swing_left, i_swing_right)
float swing_low = ta.pivotlow(low, i_swing_left, i_swing_right)
bool near_resistance = math.abs(close - nearest_resistance) / close * 100 < i_level_proximity
bool near_support = math.abs(close - nearest_support) / close * 100 < i_level_proximity
bool sweep_high = high > nearest_resistance and close < nearest_resistance
bool sweep_low = low < nearest_support and close > nearest_support
Structure components:
Swing Points: Key highs and lows defining market structure
Level Proximity: Distance to nearest support/resistance
Liquidity Sweeps: Price moves beyond levels that quickly reverse
Break of Structure: Confirms trend changes
Structure Score: Cumulative structural confirmation (0-3 points)
The structure layer ensures entries occur at technically significant levels.
5. Signal Qualification System
All layers combine to produce a comprehensive qualification score:
// Total scores (max 14)
int bull_total = (
trend_bull_score + momentum_bull_score + volume_score + structure_score +
(near_support ? 1 : 0) + (sweep_low ? 1 : 0) + (rr_ratio >= i_min_rr ? 1 : 0)
)
int bear_total = (
trend_bear_score + momentum_bear_score + volume_score + structure_score +
(near_resistance ? 1 : 0) + (sweep_high ? 1 : 0) + (rr_ratio >= i_min_rr ? 1 : 0)
)
Qualification criteria:
Trend Score (0-5 points): Directional bias strength
Momentum Score (0-3 points): Timing confirmation
Volume Score (0-3 points): Participation confirmation
Structure Score (0-3 points): Level confirmation
Level Proximity (1 point): Entry at key level
Liquidity Sweep (1 point): Institutional activity
Risk/Reward (1 point): Adequate profit potential
Maximum Score: 14 points for perfect confluence
6. Quality Grading System
Signals are graded based on their qualification score:
// Quality grades
string bull_grade = bull_total >= 12 ? "A+" :
bull_total >= 10 ? "A" :
bull_total >= 8 ? "B" :
bull_total >= 6 ? "C" : "D"
string bear_grade = bear_total >= 12 ? "A+" :
bear_total >= 10 ? "A" :
bear_total >= 8 ? "B" :
bear_total >= 6 ? "C" : "D"
Grade meanings:
A+ (12-14 points): Exceptional setup with maximum confluence
A (10-11 points): High-quality setup with strong confluence
B (8-9 points): Good setup with moderate confluence
C (6-7 points): Acceptable setup with basic confluence
D (0-5 points): Weak setup, avoid trading
Only B-grade and above signals are typically considered for trading.
7. Risk/Reward Validation
Each signal is validated for adequate profit potential:
// Risk/Reward calculation
float atr_val = ta.atr(14)
float stop_distance = atr_val * i_stop_mult
float target_distance = atr_val * i_target_mult
float rr_ratio = target_distance / stop_distance
// RR validation
bool valid_rr = rr_ratio >= i_min_rr
RR features:
ATR-Based Stops: Dynamic stop placement based on volatility
Multiple Targets: Primary and secondary profit targets
Minimum RR Ratio: Configurable minimum (default 1.5:1)
RR Validation: Signals without adequate RR are disqualified
Visual Targets: Clear stop and target levels on chart
Visual Elements
Signal Markers: Clear entry signals with quality grades
Entry Zones: Shaded areas showing optimal entry regions
Risk Levels: Visual stop loss and target levels
Quality Meter: Real-time confluence score display
Background Colors: Signal strength background shading
Dashboard: Comprehensive metrics panel
Premium Signals: Special markers for A+ grade setups
The dashboard displays:
1. Current signal qualification scores
2. Quality grades and confluence percentages
3. Individual layer scores (trend, momentum, volume, structure)
4. Risk/Reward ratio and validation status
5. Nearest support/resistance levels
6. Volume analysis and session context
7. Signal cooldown status
8. Premium signal indicators
Input Parameters
Trend Settings:
Fast MA Period: Short-term trend (default: 21)
Slow MA Period: Medium-term trend (default: 55)
ADX Period: Trend strength (default: 14)
ADX Threshold: Minimum trend strength (default: 25)
Momentum Settings:
RSI Period: Momentum oscillator (default: 14)
Stochastic K/D: Entry timing (default: 14/3)
MACD Fast/Slow/Signal: Trend acceleration (default: 12/26/9)
Structure Settings:
Swing Left/Right: Pivot point detection (default: 10/5)
Level Proximity %: Distance to key levels (default: 0.5%)
Max Levels: Maximum swing levels to track (default: 20)
Qualification Settings:
Minimum Score: Required qualification score (default: 6)
Signal Cooldown: Bars between signals (default: 5)
Minimum R:R: Required risk/reward ratio (default: 1.5)
Require Confirmation: Wait for bar close (default: true)
How to Use This Indicator
Step 1: Monitor Signal Quality
Watch for B-grade or higher signals. A-grade signals offer the highest probability but occur less frequently. Focus on quality over quantity - one A-grade signal is worth ten C-grade signals.
Step 2: Verify Layer Alignment
Check the dashboard to see which layers are contributing to the signal. The best signals have confirmation from all four layers (trend, momentum, volume, structure).
Step 3: Assess Risk/Reward
Ensure the signal offers adequate profit potential. The indicator automatically validates RR ratios, but you should manually verify that targets make sense in the current market context.
Step 4: Time Entry with Structure
Use the entry zones and structure levels to time your entry precisely. The best entries occur when price is near key support/resistance levels or after liquidity sweeps.
Step 5: Manage Risk Dynamically
Use the visual stop and target levels as guidelines, but adjust based on your personal risk tolerance and account size. Never risk more than you're comfortable losing.
Step 6: Track Premium Signals
Pay special attention to A+ grade premium signals. These rare setups with maximum confluence often lead to the largest moves and deserve larger position sizes.
Best Practices
Be patient for A-grade signals rather than forcing mediocre trades
Use the qualification score as your primary filter - ignore signals below your minimum threshold
Combine with your own analysis for additional confirmation
Adjust the minimum score based on market conditions - higher in choppy markets, lower in strong trends
Keep a trade journal to track which grade performs best in each market condition
Use the cooldown period to avoid overtrading - quality signals require patience
Pay attention to volume confirmation - signals without volume support often fail
Structure is key - signals at major levels have higher success rates
Liquidity sweeps provide high-probatility reversal opportunities
Always respect the risk/reward validation - poor RR setups destroy accounts
Strategy Integration
This indicator is designed to enhance any trading system:
Use as a signal filter for existing strategies
Import quality scores to weight trade decisions
Combine with trend-following systems for entry timing
Use structure levels for stop placement in other systems
Integrate volume analysis for signal confirmation
Apply risk/reward validation to all trades
Use premium signals as standalone trade opportunities
Export layer scores for custom signal development
The indicator includes 12 export functions for integration:
Bull/Bear Score Export: Total qualification scores
Quality Grade Export: Letter grade as numeric value
Trend Score Export: Trend layer score
Momentum Score Export: Momentum layer score
Volume Score Export: Volume layer score
Structure Score Export: Structure layer score
RR Ratio Export: Current risk/reward ratio
Signal Export: Binary signal output
Premium Signal Export: A+ grade signal flag
Technical Implementation
Built with Pine Script v6 featuring:
Multi-layer signal analysis across four independent systems
Dynamic qualification scoring with configurable weights
Advanced market structure detection with pivot points
Volume analysis with session context
Risk/reward validation with ATR-based calculations
Comprehensive visualization with entry zones and risk levels
Real-time dashboard with 12 key metrics
Alert conditions for all signal types and grades
Export functions for strategy integration
Premium signal detection for exceptional setups
The code uses confirmed bars for all calculations to prevent repainting and ensure reliable signals.
Originality Statement
This indicator is original in its comprehensive approach to signal qualification and multi-layer confluence analysis. While individual components (RSI, MACD, ADX, etc.) are established tools, this indicator is justified because:
It synthesizes four distinct analytical layers into a unified qualification system
The scoring system provides objective, numerical signal evaluation
Quality grading transforms subjective analysis into systematic decision-making
Risk/reward validation ensures only profitable setups are considered
Structure analysis integration provides context for market microstructure
Volume layer adds confirmation often missing from signal systems
Premium signal detection identifies exceptional opportunities
Comprehensive visualization makes complex analysis accessible
Export functions enable integration with any trading system
Each layer contributes unique insights: trend provides direction, momentum provides timing, volume provides confirmation, and structure provides context
The indicator's value lies in transforming signal evaluation from art to science - providing traders with a systematic, objective way to identify and focus only on the highest probability trading opportunities.
Disclaimer
This indicator is provided for educational and informational purposes only. It is not financial advice or a recommendation to buy or sell any financial instrument. Signal qualification is a tool for improving trade selection, not a guarantee of success.
Even high-quality signals can fail due to unexpected market events, news, or changes in market conditions. Past performance of high-grade signals does not guarantee future results. The indicator's signals are mathematical calculations based on historical patterns and should be used in conjunction with proper risk management.
Always use stop losses and position sizing appropriate for your account size and risk tolerance. Never risk more than you can afford to lose on any single trade, regardless of signal quality.
The author is not responsible for any losses incurred from using this indicator. Users assume full responsibility for all trading decisions made using this system.
-Made with passion by officialjackofalltrades
インジケーター
Bollinger Bands Bull/Bear B2Bollinger Bands Bull/Bear
by MasterTony
Overview & How It Works:
This indicator enhances classic Bollinger Bands by the legendary John Bollinger with emphasizing dynamic bull/bear coloring, gradient strength fills, overextension highlights, and an orange squeeze overlay to visualize volatility contraction.
Core Calculations:
Basis Line: User-selectable moving average (SMA by default) of the source (close by default).
Upper / Lower Bands: Basis ± (Multiplier × Standard Deviation over the chosen length). Default multiplier = 2.0.
Bull / Bear State Determination: Price position relative to the basis and outer or lower bollinger bands, smoothed with a short EMA.
Hysteresis is applied to prevent rapid flipping during consolidation.
Result: stable bullish state when price is convincingly above the basis, bearish when below.
Proximity & Gradient Strength: Distance from price to each band is measured and normalized against current band width.
The closer price is to a band, the stronger the signal and the more opaque the fill becomes.
Colored Band Fills: Bullish state → mint-green fills around both bands (brighter/opaquer when price hugs the upper band).
Bearish state → red fills around both bands (brighter/opaquer when price hugs the lower band).
Special Overextension Fill:
When price is very close (>85%) to the "active" band (upper in bull, lower in bear) and the state is confirmed, a Brighter gradient of the band green (bull) or lred (bear).
Strong Vs Weak Bollinger
Thicker the Bollinger Band stronger the trend, thinner the weaker. Gradient going from brighter to more transparent highlights potential exhaustion of strong Bollinger.
Squeeze Detection (Orange Overlay):
Bollinger Band Width Percentile (BBWP) is calculated over a user-defined lookback (default 100 bars).
Squeeze = BBWP ≤ 25% (bands are historically narrow).
Tight squeeze = BBWP < 15% → brighter orange.
Orange fill covers the entire area between upper and lower bands during squeeze periods.
Toggle available to hide squeeze fills if desired.
How to Read & Trade This Indicator
Visual Interpretation:
Green-dominant chart (mint fills + possible light-green basis-to-band fill) = bullish bias. The brighter and fuller the green, the stronger the momentum (price pushing against or touching the upper band).
Red-dominant chart (red fills + possible light-red basis-to-band fill) = bearish bias. Brighter/fuller red = stronger downward pressure.
Light special fills (light green or light red from basis to band) = overextension zone. Often seen near trend extremes — watch for continuation (breakout) or reversal (failure to hold the band).
Orange overlay = low volatility / squeeze. Two shades:
Lighter orange = regular squeeze (potential move brewing).
Brighter orange = very tight squeeze (high probability of imminent explosive move).
Trading Guidelines:
Trend Following (Shows Bull Zone and Bear Zones):
In green fills → favor longs or hold existing longs.
In red fills → favor shorts or hold existing shorts.
Strength increases as fills become more opaque (price near the outer band).
Squeeze Breakouts (Highest Probability Setups):
Wait for orange squeeze to appear.
When price closes outside the bands (breakout), enter in the direction of the break.
Bias the trade toward the prevailing color:Breakout upward during green fills = strong long signal.
Breakout downward during red fills = strong short signal.
If breakout direction opposes the color bias, be cautious (lower probability).
Entry/Exits:
Follow the Band color, Band color with special fill green or red is strong to determining Bull or Bear states. Green=price up Red= Price down
Risk Management:
Use the basis line as dynamic support/resistance.
Stops can be placed just beyond the opposite band or basis during strong trends.
Combine with volume or other confirmation for higher conviction.
This visual upgrade makes Bollinger Bands far more intuitive — the chart literally colors itself bullish or bearish while highlighting volatility cycles and overextension zones. Great for trend, breakout, and mean-reversion strategies across any timeframe.
Enjoy fellow traders, this is V1 more versions will be updated.
Please also boost and comment would love your ideas on advancements to this.
Cheers,
MasterTony インジケーター
Aura: Adaptive Statistical Smoother [Pineify]Aura: Adaptive Statistical Smoother
The Aura: Adaptive Statistical Smoother is an overlay trend-following indicator that combines a forward-backward zero-lag EMA approximation with an R-Squared trend filter to produce an adaptive moving average that tightly tracks price during trending markets and deliberately diverges during ranging conditions — solving the core problem of traditional moving averages that generate excessive whipsaw signals in sideways price action. Instead of using a fixed smoothing period or a single-pass EMA, the indicator first constructs a bidirectional (zero-phase-shift) EMA baseline that virtually eliminates the lag inherent in standard exponential averages, then modulates how closely the final Aura MA follows this baseline based on the real-time R-Squared coefficient of determination. When R-Squared confirms a strong linear trend, the Aura MA converges toward the zero-lag target proportionally to trend strength; when R-Squared indicates a ranging market, the MA actively pushes away from price in the last known trend direction, creating a natural buffer zone that suppresses false crossovers. Dynamic standard-deviation volatility bands and R-Squared-filtered buy/sell signals complete the system, giving traders a statistically grounded, self-adjusting trend tool with built-in noise rejection.
Key Features
Forward-backward zero-lag EMA approximation — a two-pass EMA computation (forward pass followed by a backward iteration over historical values) that closely approximates a bidirectional filter, virtually eliminating the phase lag that causes standard EMAs to react late to trend changes.
R-Squared adaptive trend filter — the Pearson correlation coefficient squared (R²) between price and bar index measures how well a linear trend fits recent data. Values above 0.5 indicate trending conditions; values below indicate ranging. This statistical metric drives the core adaptive behavior of the Aura MA.
Dual-regime moving average — during trending markets (R² > 0.5), the Aura MA blends toward the zero-lag target proportionally to R², tracking price closely. During ranging markets (R² ≤ 0.5), the MA diverges from price in the last known direction, creating a buffer that prevents whipsaw crossovers.
Dynamic volatility bands — standard deviation of the source price over the statistical window, scaled by a user-defined multiplier, creates upper and lower bands that automatically expand during volatile periods and contract during quiet ones.
R-Squared-filtered buy/sell signals — crossover signals between price and the Aura MA are only generated when R² exceeds 0.3, ensuring signals fire only when there is statistically meaningful trend strength and suppressing noise during flat markets.
Trend-adaptive coloring — the Aura MA line, volatility cloud fill, and bar colors all dynamically switch between bullish and bearish colors based on the current trend state, providing instant visual identification of the prevailing direction.
How It Works
The indicator follows a multi-stage calculation pipeline that transforms raw price data into an adaptive, statistically filtered trend line:
Forward-backward zero-lag baseline: A standard EMA is first computed on the source price. Then a second pass iterates backward over the historical EMA values, applying the same EMA alpha (2 / (smooth + 1)) at each step across the lookback window. This two-pass approach approximates a zero-phase-shift filter — the resulting baseline tracks price turns almost immediately, without the half-period delay of a conventional EMA. This baseline serves as the "target" that the adaptive Aura MA will converge toward when the market is trending.
R-Squared trend detection: The Pearson correlation between closing prices and bar indices over the statistical window is squared to produce R². This coefficient of determination measures the proportion of price variance explained by a linear trend. R² near 1.0 means price is moving in a clean, directional manner; R² near 0.0 means price is oscillating without a clear direction. The 0.5 threshold divides the market into "trending" and "ranging" regimes.
Adaptive MA computation: In trending mode (R² > 0.5), the Aura MA is computed as a weighted blend: R² × target + (1 − R²) × previous Aura MA. Stronger trends (higher R²) pull the MA closer to the zero-lag target; weaker trends allow it to lag slightly, providing natural smoothing. In ranging mode (R² ≤ 0.5), the MA moves away from price by the magnitude of the target's recent change, in the direction of the last known trend bias. This deliberate divergence creates separation between price and the MA, preventing the repeated false crossovers that plague fixed-parameter moving averages in choppy markets.
Volatility bands and signal generation: Standard deviation bands are added around the Aura MA to visualize the current volatility regime. Buy and sell signals are generated on price crossovers of the Aura MA, but only when R² exceeds 0.3 — a secondary filter that ensures even the crossover signals carry minimum statistical trend evidence.
Trading Ideas and Insights
Trend-following entries with lag reduction: The zero-lag baseline allows the Aura MA to respond to trend initiations significantly faster than a standard EMA of equivalent smoothing. When a BUY signal fires (price crosses above the Aura MA with R² > 0.3), the entry is closer to the actual trend start than what a conventional moving average crossover would provide, improving the risk/reward ratio of trend-following trades.
Whipsaw avoidance in ranging markets: The adaptive divergence mechanism during low-R² periods is specifically designed to prevent the most common failure mode of moving average systems — repeated false crossovers during sideways consolidation. Traders can trust that when a signal does fire, the statistical environment supports a directional move.
Volatility band breakout confirmation: When price breaks above the upper band or below the lower band while the Aura MA is already in the corresponding trend state, it confirms a high-volatility directional expansion. These breakouts can be used to add to existing positions or to set trailing stops at the opposite band.
R-Squared as a standalone filter: Even without acting on the buy/sell signals, traders can use the implicit R-Squared regime (visible through the MA's behavior — tight tracking vs. divergence) as a filter for other strategies. Apply your existing entry rules only when the Aura MA is tightly tracking price (trending regime), and stand aside when the MA visibly separates from price (ranging regime).
Multi-timeframe trend alignment: Apply the Aura indicator on both a higher timeframe (e.g., daily) and a lower timeframe (e.g., 1-hour). Take lower-timeframe BUY signals only when the higher-timeframe Aura MA is in bullish state, and SELL signals only when the higher-timeframe is bearish. This multi-timeframe alignment leverages the adaptive nature of the indicator across different time horizons.
How Multiple Indicators Work Together
The Aura indicator integrates three distinct analytical components into a unified adaptive system, each addressing a specific weakness of traditional moving averages:
Forward-backward zero-lag EMA (lag elimination): Standard moving averages inherently lag price by approximately half their lookback period. The bidirectional EMA approximation addresses this by running a second smoothing pass in reverse over historical values, canceling out the phase shift. This gives the Aura MA a responsive baseline to track during trends — without the noise sensitivity that comes from simply using a very short-period EMA.
R-Squared trend filter (regime detection): The R-Squared coefficient provides an objective, statistical answer to the question "is the market trending right now?" This replaces subjective visual assessment or fixed-threshold approaches (like ADX) with a measure rooted in linear regression theory. R² directly controls how the Aura MA behaves — it is not merely a signal filter but the core adaptive mechanism that switches the MA between trend-tracking and range-diverging modes.
Standard deviation volatility bands (context visualization): The bands add a volatility dimension that neither the zero-lag baseline nor the R-Squared filter provides. They show traders the expected range of price movement around the Aura MA, helping to distinguish between normal retracements within a trend (price stays within bands) and genuine trend reversals (price breaks through bands and crosses the MA).
The synergy is structural: zero-lag EMA (responsive baseline) → R-Squared (regime classification) → adaptive blending/divergence (the Aura MA itself) → volatility bands (context envelope) → R²-filtered crossover signals (actionable entries/exits). The zero-lag baseline ensures the MA has a fast, accurate target to track; R-Squared determines whether to track it or diverge; and the volatility bands provide the visual context for interpreting the MA's position relative to price. Each component compensates for a specific weakness — lag, false signals in ranges, and lack of volatility context — that would undermine the system if any single component were used alone.
Unique Aspects
Statistical regime switching: Unlike adaptive moving averages that use volatility or momentum to adjust their speed (e.g., KAMA, VIDYA), the Aura MA uses R-Squared — a measure of trend linearity — to switch between two fundamentally different behaviors: convergence toward a target during trends and deliberate divergence during ranges. This is a qualitatively different approach that directly addresses the root cause of whipsaw (lack of trend) rather than a symptom (high volatility).
Bidirectional EMA approximation in Pine Script: True zero-phase-shift filters require processing the entire dataset in both directions, which is not natively possible in real-time bar-by-bar computation. The forward-backward loop in this indicator approximates this by iterating over historical forward-EMA values within the lookback window, achieving near-zero lag without requiring future data — a practical implementation of signal processing theory within Pine Script's constraints.
Directional divergence mechanism: During ranging markets, the Aura MA does not simply freeze or slow down — it actively moves away from price in the last known trend direction. This creates increasing separation that requires a genuine trend resumption (not just noise) to produce a crossover, providing a self-adjusting buffer proportional to the ranging market's volatility.
Dual-threshold R-Squared filtering: The indicator uses two R-Squared thresholds for different purposes: 0.5 for the MA's adaptive regime switch (trending vs. ranging behavior) and 0.3 for signal generation (minimum trend evidence for crossover signals). This layered approach means the MA adapts its behavior at a stricter threshold while still allowing signals in moderately trending conditions, balancing responsiveness with noise rejection.
How to Use
Add the indicator to your chart. It overlays directly on the price chart, displaying the Aura MA line, upper and lower volatility bands, and a shaded volatility cloud between the bands.
Observe the Aura MA line (thick colored line). When it is green and tightly tracking price, the market is in a statistically confirmed uptrend. When it is red and tracking price closely, the market is in a confirmed downtrend. When the MA visibly separates from price, the R-Squared filter has detected a ranging market and the MA is in divergence mode.
Watch for BUY signals (green "BUY" labels below bars) — these fire when price crosses above the Aura MA and R-Squared exceeds 0.3, indicating a bullish crossover with minimum statistical trend support. Consider entering long positions or closing short positions.
Watch for SELL signals (red "SELL" labels above bars) — these fire when price crosses below the Aura MA and R-Squared exceeds 0.3, indicating a bearish crossover with trend confirmation. Consider entering short positions or closing long positions.
Use the volatility bands (shaded cloud) to gauge the expected price range around the Aura MA. Price touching the upper band in an uptrend suggests extended momentum; price touching the lower band in a downtrend suggests extended selling pressure. Reversals from band extremes back toward the MA can serve as mean-reversion opportunities within the prevailing trend.
Monitor bar colors for a quick visual scan of the current trend state across the chart — green bars indicate bullish trend, red bars indicate bearish trend.
Adjust the Statistical Window to match your trading timeframe. Shorter windows (10–15) make the R-Squared filter more responsive to recent price behavior — suitable for intraday or short-term swing trading. Longer windows (25–50) provide a more stable trend assessment — suitable for position trading on daily or weekly charts.
Customization
Statistical Window (default: 20): The lookback period for both the R-Squared calculation and the standard deviation bands. This is the most impactful parameter. Shorter values make the indicator more responsive — the R-Squared filter reacts faster to regime changes and the volatility bands adjust more quickly. Longer values produce smoother, more stable readings that filter out short-term noise but may delay regime detection. Start with 20 for daily charts and adjust based on your asset's typical trend duration.
Forward-Backward Smoothing (default: 10): Controls the EMA period used in the zero-lag approximation. Lower values (5–7) produce a baseline that tracks price very closely, making the Aura MA highly responsive during trends but potentially more sensitive to noise. Higher values (15–20) produce a smoother baseline with slightly more residual lag but better noise rejection. The interaction between this parameter and the Statistical Window determines the overall character of the indicator.
Volatility Multiplier (default: 1.5): Scales the standard deviation bands around the Aura MA. Higher values (2.0–3.0) produce wider bands that contain more price action — useful for volatile assets or for identifying only extreme deviations. Lower values (0.5–1.0) produce tighter bands that price breaks more frequently — useful for identifying smaller volatility expansions or for more active trading styles.
Bullish / Bearish Colors: Fully customizable colors applied to the Aura MA line, volatility bands, cloud fill, signal labels, and bar coloring. Adjust to match your chart theme or to improve visibility on different background colors.
Conclusion
The Aura: Adaptive Statistical Smoother brings a statistically rigorous approach to trend following by combining a forward-backward zero-lag EMA approximation with an R-Squared-driven adaptive regime filter. The zero-lag baseline eliminates the inherent delay of conventional moving averages, while the R-Squared coefficient provides an objective, real-time assessment of whether the market is trending or ranging. During trends, the Aura MA converges toward the responsive baseline proportionally to trend strength; during ranges, it deliberately diverges to create a whipsaw-resistant buffer zone. Dynamic volatility bands add a contextual envelope, and dual-threshold R-Squared filtering ensures that buy and sell signals carry minimum statistical trend evidence. Whether used as a standalone trend-following system or as an adaptive trend filter for other strategies, the Aura indicator provides a self-adjusting framework that adapts its behavior to the current market regime — tracking trends closely when they exist and stepping aside when they do not.
インジケーター
Regime Classifier [JOAT]Regime Classifier
Introduction
The Regime Classifier is a sophisticated market state detection system designed to identify and classify market conditions into distinct operational regimes. Understanding the current market regime is perhaps the most critical factor in successful trading - a strategy that works beautifully in a trending market will fail miserably in a ranging market, and vice versa. This indicator solves that fundamental problem by providing clear, actionable classification of market states, allowing traders to adapt their approach to current conditions.
This tool is built for traders who understand that markets are not random but move through distinct phases, each requiring different strategies and risk management approaches. Whether you're a systematic trader needing regime filters, a discretionary trader seeking market context, or a portfolio manager adjusting exposure, this classifier provides the institutional-grade market intelligence needed to navigate any market environment successfully.
Why This Indicator Exists
Most traders apply the same strategy regardless of market conditions, then wonder why their performance is inconsistent. This indicator addresses that critical flaw by:
Regime Classification: Identifies four distinct market states with clear characteristics
Regime Strength: Measures how strongly the market exhibits regime characteristics
Regime Persistence: Tracks how long the current regime has been in place
Regime Quality: Evaluates the reliability of the current regime classification
Session Awareness: Considers session context for regime analysis
Regime Transitions: Detects and signals regime changes for strategy adaptation
The classifier transforms the complex, often subjective process of market analysis into an objective, systematic framework that can be consistently applied across all instruments and timeframes.
Core Components Explained
1. ADX-Based Trend Detection
The Average Directional Index (ADX) is the primary tool for trend detection:
// ADX calculation
float atr_val = ta.rma(ta.tr(true), i_adx_period)
float up_move = high - high
float down_move = low - low
float plus_dm = up_move > down_move and up_move > 0 ? up_move : 0
float minus_dm = down_move > up_move and down_move > 0 ? down_move : 0
float plus_di = 100 * ta.rma(plus_dm, i_adx_period) / atr_val
float minus_di = 100 * ta.rma(minus_dm, i_adx_period) / atr_val
float adx = 100 * ta.rma(math.abs(plus_di - minus_di) / (plus_di + minus_di), i_adx_period)
ADX components:
ADX Value: Trend strength (0-100), regardless of direction
+DI: Bullish directional movement
-DI: Bearish directional movement
Trend Threshold: Minimum ADX for trend classification (default 25)
Directional Bias: +DI vs -DI for trend direction
ADX above 25 indicates a trending market, while below 25 suggests ranging or volatile conditions.
2. ATR-Based Volatility Analysis
The Average True Range (ATR) measures volatility and helps distinguish between different non-trending states:
// ATR analysis
float atr_current = ta.atr(i_atr_period)
float atr_average = ta.sma(atr_current, i_atr_period * 3)
float atr_ratio = atr_average > 0 ? atr_current / atr_average : 1.0
// Volatility thresholds
float expansion_threshold = i_atr_expansion_mult
float contraction_threshold = i_atr_contraction_mult
ATR components:
Current ATR: Recent volatility measurement
Average ATR: Long-term volatility baseline
ATR Ratio: Current volatility relative to average
Expansion Threshold: Ratio indicating high volatility (default 1.4)
Contraction Threshold: Ratio indicating low volatility (default 0.6)
ATR analysis helps distinguish between ranging (low volatility) and volatile (high volatility) markets when ADX is below the trend threshold.
3. Regime Classification Logic
The indicator classifies markets into four distinct regimes:
// Regime classification
int market_regime = 0
if adx >= i_adx_trend
market_regime := 1 // Trending
else if atr_ratio >= expansion_threshold and adx < i_adx_trend
market_regime := 3 // Volatile
else if atr_ratio <= contraction_threshold and adx < i_adx_trend
market_regime := 2 // Ranging
else
market_regime := 0 // Neutral
Regime types:
Trending (ADX ≥ 25): Strong directional movement with clear trend
Ranging (ADX < 25, ATR ratio ≤ 0.6): Low volatility, sideways movement
Volatile (ADX < 25, ATR ratio ≥ 1.4): High volatility, erratic movement
Neutral (ADX < 25, 0.6 < ATR ratio < 1.4): Transition between defined states
Each regime has distinct characteristics that require different trading approaches.
4. Regime Strength Measurement
Not all regimes are created equal - some are stronger and more reliable than others:
// Regime strength calculation
float regime_strength = 0.0
switch market_regime
1 => regime_strength := math.min(adx / 50.0 * 100, 100) // Trending strength
2 => regime_strength := math.min((1 - atr_ratio) / (1 - contraction_threshold) * 100, 100) // Ranging strength
3 => regime_strength := math.min((atr_ratio - 1) / (expansion_threshold - 1) * 100, 100) // Volatile strength
0 => regime_strength := 50.0 // Neutral default
Strength interpretation:
Trending Strength: Based on ADX value (higher ADX = stronger trend)
Ranging Strength: Based on how low volatility is (lower ATR = stronger range)
Volatile Strength: Based on how high volatility is (higher ATR = stronger volatility)
Neutral Strength: Fixed at 50% as baseline
Strength Range: 0-100% indicating regime confidence
Higher strength values indicate more reliable regime classification.
5. Regime Persistence Analysis
The duration of a regime provides additional context about its reliability:
// Regime persistence tracking
var int regime_bars = 0
var int regime_start_bar = 0
if market_regime == market_regime
regime_bars := regime_bars + 1
else
regime_bars := 1
regime_start_bar := bar_index
// Persistence score
float persistence_score = math.min(float(regime_bars) / i_persistence_lookback * 100, 100)
Persistence features:
Regime Bars: Number of consecutive bars in current regime
Regime Start: When the current regime began
Persistence Score: Normalized duration (0-100%)
Lookback Period: Reference period for normalization (default 50)
Mature Regimes: Higher persistence indicates established conditions
Long-lasting regimes are more reliable than newly formed ones.
6. Regime Quality Assessment
Quality evaluates how well the current market fits the regime characteristics:
// Quality assessment
float quality_score = 0.0
float adx_quality = adx / 50.0 * 50 // 50% weight
float atr_quality = market_regime == 2 ? (1 - atr_ratio) / (1 - contraction_threshold) * 50 :
market_regime == 3 ? (atr_ratio - 1) / (expansion_threshold - 1) * 50 : 25
quality_score := adx_quality + atr_quality
Quality components:
ADX Quality: How well trend strength matches regime expectations
ATR Quality: How well volatility matches regime expectations
Quality Score: Combined assessment (0-100%)
High Quality: Clear regime characteristics
Low Quality: Ambiguous or transitioning conditions
High quality scores indicate clear, unambiguous market conditions.
7. Session Context Integration
Market behavior varies significantly across trading sessions:
// Session analysis
bool asian_session = time(timeframe.period, "0000-0800")
bool london_session = time(timeframe.period, "0700-1600")
bool ny_session = time(timeframe.period, "1200-2100")
// Session-specific adjustments
float session_multiplier = 1.0
if london_session
session_multiplier := 1.2 // Higher volatility expected
else if asian_session
session_multiplier := 0.8 // Lower volatility expected
Session features:
Session Detection: Identifies major trading sessions
Session Multipliers: Adjusts expectations based on session characteristics
Session Persistence: Tracks regime duration within current session
Session Quality: Evaluates regime quality within session context
Session Transitions: Identifies regime changes at session opens/closes
Session context helps interpret regime changes and anticipate behavior.
Visual Elements
Regime Histogram: Color-coded bars showing current regime
Strength Meter: Visual representation of regime strength
Persistence Line: Shows regime duration over time
Quality Gauge: Quality score visualization
Background Colors: Regime-based background shading
Session Markers: Visual session boundaries
Dashboard: Real-time regime metrics
Transition Alerts: Visual regime change notifications
The dashboard displays:
1. Current market regime and confidence
2. Regime strength and persistence
3. Quality score and trend direction
4. Session context and behavior
5. Regime history and transitions
6. Recommended strategies for current regime
7. Risk management adjustments
8. Regime forecast based on patterns
Input Parameters
ADX Settings:
ADX Period: Trend strength calculation (default: 14)
Trend Threshold: Minimum ADX for trend regime (default: 25)
ADX Smoothing: Additional smoothing for ADX (default: 3)
ATR Settings:
ATR Period: Volatility calculation (default: 14)
Expansion Multiplier: High volatility threshold (default: 1.4)
Contraction Multiplier: Low volatility threshold (default: 0.6)
Analysis Settings:
Persistence Lookback: Reference for persistence score (default: 50)
Quality Smoothing: Smoothing for quality calculation (default: 5)
Session Awareness: Enable session analysis (default: true)
Visual Settings:
Color Scheme: Customizable regime colors
Background Shading: Enable regime backgrounds
Dashboard Display: Show metrics panel
Alert Settings: Configure regime change alerts
How to Use This Indicator
Step 1: Identify Current Regime
Check the dashboard for the current market regime. Each regime requires a different approach:
Trending: Use trend-following strategies, let winners run
Ranging: Use mean-reversion strategies, take profits at levels
Volatile: Reduce position size, use wider stops, or avoid trading
Neutral: Wait for clarity, reduce trading activity
Step 2: Assess Regime Strength
Higher strength indicates more reliable conditions. In strong regimes (80%+), you can be more aggressive with position sizing. In weak regimes (<50%), reduce exposure and wait for confirmation.
Step 3: Monitor Persistence
Newly formed regimes (<10 bars) may be false signals. Mature regimes (>20 bars) are more established and reliable. Consider regime persistence in your strategy selection.
Step 4: Evaluate Quality
High quality scores (>75%) indicate clear market conditions. Low quality scores (<50%) suggest ambiguity - reduce trading or wait for clarity.
Step 5: Consider Session Context
Regimes that persist across multiple sessions are more significant. Regime changes at session opens often set the tone for the session.
Step 6: Watch for Transitions
Regime transitions signal strategy changes. A shift from trending to ranging requires switching from trend-following to range-bound strategies.
Best Practices
Always adapt your strategy to the current regime - don't use a trending strategy in ranging markets
High strength + high quality = maximum confidence in regime classification
Low persistence regimes (<10 bars) may be false - wait for confirmation
Session transitions often trigger regime changes - be alert at session opens
Volatile regimes are dangerous for most traders - consider reducing activity
Regime persistence is key - the longer a regime persists, the more reliable it is
Quality scores below 50% suggest waiting for clarity
Combine regime analysis with your existing strategy for better results
Keep a regime journal to track how each instrument behaves in different regimes
Use regime transitions as signals to adjust your entire trading approach
Strategy Applications by Regime
Trending Regime:
Trend-following strategies (moving averages, ADX, momentum)
Let winners run to maximum targets
Use trailing stops to capture extended moves
Add to positions on pullbacks in trend direction
Higher position sizing due to clear direction
Ranging Regime:
Mean-reversion strategies (RSI, Stochastic, Bollinger Bands)
Take profits at support/resistance levels
Use fixed targets - don't let winners turn into losers
Fade extreme moves toward the range middle
Smaller position sizing due to limited moves
Volatile Regime:
Reduce position size significantly (50% or less)
Use wider stops to avoid premature exits
Consider sitting out until conditions improve
Focus on volatility breakout patterns if trading
Quick profit taking - volatile conditions reverse quickly
Neutral Regime:
Wait for clarity before taking new positions
Manage existing positions more actively
Reduce trading frequency
Look for regime transition signals
Focus on longer timeframe analysis for direction
Technical Implementation
Built with Pine Script v6 featuring:
Advanced ADX calculation with directional movement analysis
Multi-timeframe ATR analysis for volatility assessment
Regime classification with confirmation logic
Strength, persistence, and quality scoring systems
Session awareness with timezone handling
Comprehensive visualization with multiple display modes
Real-time dashboard with 10 key metrics
Alert conditions for regime changes and thresholds
Export functions for strategy integration
Historical regime tracking and pattern recognition
The code uses confirmed bars for all calculations to prevent repainting and ensure reliable regime classification.
Originality Statement
This indicator is original in its comprehensive approach to regime classification and market state analysis. While ADX and ATR are established tools, this indicator is justified because:
It synthesizes trend and volatility analysis into a unified regime classification system
The strength, persistence, and quality scoring provides multi-dimensional regime assessment
Session awareness adds critical context often missing from regime analysis
Regime transition detection helps traders adapt strategy changes proactively
The four-regime classification (Trending, Ranging, Volatile, Neutral) covers all market states
Quality assessment helps distinguish between clear and ambiguous market conditions
Persistence analysis identifies mature, reliable regimes versus new, potentially false ones
Comprehensive visualization makes complex regime analysis accessible and actionable
Export functions enable regime-based strategy filtering and adaptation
Each component provides unique insights: ADX shows trend, ATR shows volatility, strength shows conviction, persistence shows duration, and quality shows clarity
The indicator's value lies in transforming the abstract concept of "market conditions" into concrete, actionable classifications that traders can use to adapt their strategies systematically and consistently.
Disclaimer
This indicator is provided for educational and informational purposes only. It is not financial advice or a recommendation to buy or sell any financial instrument. Regime classification is a tool for understanding market conditions, not a prediction system.
Market regimes can change suddenly due to news events, economic data, or changes in market structure. Past regime behavior does not guarantee future patterns. The indicator's classifications are mathematical calculations based on historical patterns and should be used in conjunction with other forms of analysis.
Always use proper risk management, including stop losses and position sizing appropriate for current market conditions. Different regimes require different risk approaches - volatile regimes may require smaller positions and wider stops.
The author is not responsible for any losses incurred from using this indicator. Users assume full responsibility for all trading decisions made using this system.
-Made with passion by officialjackofalltrades
インジケーター
Directional Bias Aggregator [JOAT]Directional Bias Aggregator
Introduction
The Directional Bias Aggregator is a sophisticated multi-timeframe bias scoring system designed to measure and aggregate directional conviction across multiple timeframes. This indicator solves the critical problem of conflicting signals across different timeframes by providing a weighted, systematic approach to bias analysis. Understanding the true directional bias requires looking beyond the current timeframe - professional traders always consider the bigger picture, and this tool brings that institutional approach to your trading.
This indicator is built for traders who understand that trends exist on multiple timeframes simultaneously and that the highest probability trades occur when these timeframes align. Whether you're a day trader needing higher timeframe context, a swing trader confirming trend direction, or a position trader assessing long-term bias, this aggregator provides the comprehensive directional intelligence needed to trade with confidence and clarity.
Why This Indicator Exists
Most traders struggle with timeframe analysis - they might see a bullish signal on the 15-minute chart but bearish conditions on the 4-hour, leading to confusion and poor decisions. This indicator addresses that problem by:
Multi-Timeframe Analysis: Evaluates bias across up to four timeframes simultaneously
Weighted Aggregation: Assigns importance to each timeframe based on trading style
Bias Scoring: Provides numerical bias scores (-100 to +100) for objective analysis
Alignment Detection: Identifies when multiple timeframes agree on direction
Trend Integration: Adds trend filter to prevent trading against major moves
Conviction Measurement: Quantifies the strength of directional bias
The aggregator transforms the complex, often subjective process of multi-timeframe analysis into an objective, systematic framework that can be consistently applied.
Core Components Explained
1. Single Timeframe Bias Calculation
Each timeframe's bias is calculated using multiple indicators:
// Single timeframe bias calculation
f_calc_bias(float src_close, float src_high, float src_low) =>
// MA trend component
float ma_fast = ta.ema(src_close, i_ma_fast)
float ma_slow = ta.ema(src_close, i_ma_slow)
float ma_diff = ma_slow != 0 ? (ma_fast - ma_slow) / ma_slow * 100 : 0
float ma_score = math.max(math.min(ma_diff * 10, 100), -100)
// Price position component
float price_pos = 0.0
if src_close > ma_fast and ma_fast > ma_slow
price_pos := 100
else if src_close < ma_fast and ma_fast < ma_slow
price_pos := -100
// ... additional price position logic
// RSI component
float rsi_val = ta.rsi(src_close, i_rsi_len)
float rsi_score = (rsi_val - 50) * 2
// MACD component
float macd_line = ta.ema(src_close, i_macd_fast) - ta.ema(src_close, i_macd_slow)
float macd_signal = ta.ema(macd_line, i_macd_sig)
float macd_hist = macd_line - macd_signal
float atr_val = ta.atr(14)
float macd_score = atr_val > 0 ? (macd_hist > 0 ?
math.min(macd_hist / atr_val * 50, 100) :
math.max(macd_hist / atr_val * 50, -100)) : 0
// Composite score
float composite = ma_score * 0.35 + price_pos * 0.30 + rsi_score * 0.15 + macd_score * 0.20
composite
Bias components:
MA Trend (35% weight): Fast/slow EMA relationship and slope
Price Position (30% weight): Price relative to moving averages
RSI Momentum (15% weight): RSI centered at 50 for directional bias
MACD Histogram (20% weight): Trend acceleration/deceleration
Score Range: -100 (strong bearish) to +100 (strong bullish)
Neutral Zone: Scores between -30 and +30 considered neutral
Each component contributes unique directional information for comprehensive analysis.
2. Multi-Timeframe Data Requests
The indicator requests bias calculations from multiple timeframes:
// Request bias from each timeframe
f_request_bias(string tf) =>
request.security(syminfo.tickerid, tf, f_calc_bias(close, high, low) ,
lookahead=barmerge.lookahead_on)
float bias_tf1 = f_request_bias(i_tf1) // Fastest timeframe
float bias_tf2 = f_request_bias(i_tf2) // Medium timeframe
float bias_tf3 = f_request_bias(i_tf3) // Slow timeframe
float bias_tf4 = f_request_bias(i_tf4) // Slowest timeframe
MTF features:
Configurable Timeframes: User-defined timeframe selection
Confirmed Bars: Uses previous bar to prevent repainting
Lookahead Management: Proper security request handling
Current TF Bias: Also calculates bias on current timeframe
Data Validation: Handles missing or invalid data gracefully
The MTF system ensures you always have the bigger picture context.
3. Weighted Aggregation System
Timeframes are weighted based on their importance:
// Normalize weights
float total_weight = i_w1 + i_w2 + i_w3 + i_w4
float w1_norm = total_weight > 0 ? i_w1 / total_weight : 0.25
float w2_norm = total_weight > 0 ? i_w2 / total_weight : 0.25
float w3_norm = total_weight > 0 ? i_w3 / total_weight : 0.25
float w4_norm = total_weight > 0 ? i_w4 / total_weight : 0.25
// Aggregate bias score
float aggregate_bias = nz(bias_tf1) * w1_norm + nz(bias_tf2) * w2_norm +
nz(bias_tf3) * w3_norm + nz(bias_tf4) * w4_norm
// Smoothed aggregate
float smooth_bias = ta.ema(aggregate_bias, 3)
Weighting features:
Customizable Weights: Assign importance to each timeframe
Automatic Normalization: Ensures weights sum to 100%
Default Weights: Higher weight to slower timeframes (15%, 25%, 30%, 30%)
Smoothing: EMA smoothing for cleaner signals
Flexibility: Adjust weights based on trading style
The aggregation system creates a single, unified bias score from all timeframes.
4. Bias Alignment Analysis
The indicator measures how many timeframes agree on direction:
// Count aligned timeframes
int bullish_count = 0
int bearish_count = 0
if nz(bias_tf1) > i_weak_thresh
bullish_count += 1
else if nz(bias_tf1) < -i_weak_thresh
bearish_count += 1
// Repeat for TF2, TF3, TF4...
// Alignment score (0-4)
int alignment_score = math.max(bullish_count, bearish_count)
// Alignment direction
int alignment_direction = bullish_count > bearish_count ? 1 :
bearish_count > bullish_count ? -1 : 0
// Perfect alignment check
bool perfect_bullish = bullish_count == 4
bool perfect_bearish = bearish_count == 4
Alignment features:
Alignment Score: Number of timeframes agreeing (0-4)
Alignment Direction: Overall consensus direction
Perfect Alignment: All timeframes agree (strongest signal)
Weak Threshold: Minimum bias for alignment (default 30)
Mixed Signals: When timeframes disagree (lower confidence)
Higher alignment scores indicate higher probability setups.
5. Trend Filter Integration
An optional trend filter prevents trading against major moves:
// Trend filter
float trend_ma = ta.ema(close, i_trend_ma)
bool above_trend = close > trend_ma
bool below_trend = close < trend_ma
float trend_distance = trend_ma != 0 ? (close - trend_ma) / trend_ma * 100 : 0
// Trend-adjusted bias
float trend_adjusted_bias = smooth_bias
if i_use_trend
if above_trend and smooth_bias > 0
trend_adjusted_bias := smooth_bias * (1 + i_trend_weight)
else if below_trend and smooth_bias < 0
trend_adjusted_bias := smooth_bias * (1 + i_trend_weight)
else if above_trend and smooth_bias < 0
trend_adjusted_bias := smooth_bias * (1 - i_trend_weight * 0.5)
else if below_trend and smooth_bias > 0
trend_adjusted_bias := smooth_bias * (1 - i_trend_weight * 0.5)
Trend filter features:
Trend MA: Long-term moving average (default 200)
Trend Weight: Bonus for trading with trend (default 20%)
Penalty System: Reduces bias when trading against trend
Trend Distance: Measures how far price is from trend
Optional: Can be disabled for counter-trend strategies
The trend filter adds an extra layer of confirmation for directional bias.
6. Conviction and Consistency Metrics
The indicator measures the strength and stability of bias:
// Confluence quality
float confluence_quality = (float(alignment_score) / 4.0) *
(math.abs(smooth_bias) / 100.0) * 100
// Bias conviction score
float conviction_score = 0.0
conviction_score += float(alignment_score) * 15 // Max 60
conviction_score += math.abs(smooth_bias) * 0.3 // Max 30
if i_use_trend
if (above_trend and smooth_bias > 0) or (below_trend and smooth_bias < 0)
conviction_score += 10 // Trend alignment bonus
conviction_score := math.min(conviction_score, 100)
// Bias consistency
var int bias_consistency_counter = 0
if smooth_bias > i_weak_thresh and smooth_bias > i_weak_thresh
bias_consistency_counter := math.min(bias_consistency_counter + 1, 20)
else if smooth_bias < -i_weak_thresh and smooth_bias < -i_weak_thresh
bias_consistency_counter := math.min(bias_consistency_counter + 1, 20)
else
bias_consistency_counter := math.max(bias_consistency_counter - 1, 0)
float bias_consistency = float(bias_consistency_counter) / 20.0 * 100
Quality metrics:
Confluence Quality: Combines alignment and strength (0-100%)
Conviction Score: Overall signal strength (0-100)
Bias Consistency: How stable the bias has been (0-100%)
Momentum: Rate of change in bias
Acceleration: Change in bias momentum
These metrics help assess signal reliability and persistence.
Visual Elements
Bias Histogram: Main bias display with gradient coloring
Conviction Ribbon: Visual representation of conviction strength
MTF Breakdown Lines: Individual timeframe bias lines
Alignment Markers: Diamonds for perfect alignment
Momentum Plot: Bias momentum visualization
Background Colors: Regime-based background shading
Dashboard: Comprehensive metrics panel
Glow Effects: Intensity-based visual enhancements
The dashboard displays:
1. Individual timeframe biases and weights
2. Aggregate bias and trend-adjusted bias
3. Alignment score and direction
4. Confluence quality percentage
5. Conviction score and consistency
6. Bias momentum and acceleration
7. Trend filter status and distance
8. Signal strength and recommendations
Input Parameters
Timeframe Settings:
Timeframe 1-4: Individual timeframes for analysis
Default: 15m, 60m, 240m, Daily
Flexible: Can be any valid timeframe combination
Weighting Settings:
TF1-TF4 Weights: Individual importance weights
Default: 15%, 25%, 30%, 30% (favoring slower timeframes)
Total: Automatically normalized to 100%
Calculation Settings:
Fast/Slow MA: Bias calculation periods (default: 8/21)
RSI Period: Momentum oscillator (default: 14)
MACD Settings: Fast/Slow/Signal (default: 12/26/9)
Threshold Settings:
Strong Bias Threshold: Strong signal level (default: 60)
Weak Bias Threshold: Minimum bias for alignment (default: 30)
Trend Weight: Bonus for trend alignment (default: 20%)
How to Use This Indicator
Step 1: Analyze Individual Timeframes
Check the dashboard to see bias on each timeframe. Look for consistency - if most timeframes show the same direction, confidence is higher.
Step 2: Check Aggregate Bias
The aggregate bias provides a unified directional score. Values above 60 indicate strong bullish bias, below -60 indicate strong bearish bias.
Step 3: Verify Alignment
Higher alignment scores (3-4 timeframes) offer the highest probability setups. Perfect alignment (4/4) often precedes strong moves.
Step 4: Assess Conviction
High conviction scores (>75%) indicate strong, consistent bias. Low conviction (<50%) suggests uncertainty - wait for clarity.
Step 5: Consider Trend Filter
If enabled, ensure bias aligns with the major trend. Trading against the trend reduces conviction and increases risk.
Step 6: Monitor Momentum
Accelerating bias in the direction of alignment suggests the move is gaining strength. Decelerating bias warns of potential reversals.
Best Practices
Perfect alignment (4/4) provides the highest probability setups
Higher timeframe bias should generally override lower timeframe signals
Increasing conviction scores suggest strengthening trends
Divergence between timeframes often precedes reversals
Use the trend filter unless you're specifically trading counter-trend setups
Bias consistency is key - look for stable, persistent bias
Sudden changes in aggregate bias often signal regime shifts
Combine with price action for optimal entry timing
Adjust timeframe weights based on your trading style
Keep a bias journal to track how different instruments behave
Trading Applications
Trend Following:
Enter when bias > 60 on at least 3 timeframes
Add to positions as conviction increases
Stay in trades as long as bias remains aligned
Exit when bias weakens or reverses on slower timeframes
Mean Reversion:
Look for extreme bias (>80 or <-80) on faster timeframes
Enter when faster timeframe bias opposes slower timeframe
Target mean reversion to neutral bias levels
Quick exits - don't fight the longer-term bias
Breakout Trading:
Wait for bias alignment across all timeframes
Enter on breakouts with supporting bias momentum
Use wider stops due to potential volatility
Scale out as bias reaches extreme levels
Strategy Integration
This indicator enhances any trading system:
Use as a directional filter for existing strategies
Import aggregate bias for trend confirmation
Use alignment score as signal strength filter
Apply conviction scoring for position sizing
Integrate trend filter for additional safety
Export individual timeframe biases for custom logic
Technical Implementation
Built with Pine Script v6 featuring:
Multi-timeframe bias calculation with proper security requests
Weighted aggregation system with automatic normalization
Advanced alignment detection with perfect alignment alerts
Trend filter integration with adjustable weighting
Conviction and consistency scoring systems
Momentum and acceleration analysis
Comprehensive visualization with multi-layer effects
Real-time dashboard with 12 key metrics
Alert conditions for all major bias events
Export functions for strategy integration
The code uses confirmed bars and proper lookahead management to prevent repainting.
Originality Statement
This indicator is original in its comprehensive approach to multi-timeframe bias aggregation and scoring. While individual components (moving averages, RSI, MACD) are established tools, this indicator is justified because:
It synthesizes bias analysis across multiple timeframes into a unified scoring system
The weighted aggregation allows customization based on trading style and preferences
Alignment detection provides objective measures of timeframe consensus
The conviction scoring system quantifies signal strength and reliability
Trend filter integration adds an extra layer of confirmation
Consistency analysis identifies stable, persistent bias versus noisy fluctuations
The dashboard presents complex multi-timeframe analysis in an accessible format
Export functions enable integration with any trading system
Each timeframe contributes unique context: faster timeframes show immediate bias, slower timeframes show established trends
The indicator solves the real problem of conflicting signals across timeframes through systematic aggregation
The indicator's value lies in transforming the complex, often confusing world of multi-timeframe analysis into a clear, objective system that traders can use to make informed decisions with confidence.
Disclaimer
This indicator is provided for educational and informational purposes only. It is not financial advice or a recommendation to buy or sell any financial instrument. Multi-timeframe analysis is a tool for understanding market context, not a prediction system.
Bias can change suddenly due to news events, economic data, or changes in market structure. Past bias patterns do not guarantee future behavior. The indicator's signals are mathematical calculations based on historical patterns and should be used in conjunction with other forms of analysis.
Always use proper risk management, including stop losses and position sizing appropriate for your account and risk tolerance. Strong bias alignment does not guarantee success - markets can remain irrational longer than you can remain solvent.
The author is not responsible for any losses incurred from using this indicator. Users assume full responsibility for all trading decisions made using this system.
-Made with passion by officialjackofalltrades
インジケーター
TetraTrend Engine [MarkitTick]💡 The TetraTrend Engine is an advanced, multifaceted overlay indicator designed to provide traders with a comprehensive view of market structure, trend direction, and institutional liquidity levels. By capturing and freezing critical moving average data at a user-defined moment in time, it transforms lagging indicators into static support and resistance frameworks. Furthermore, it integrates a sophisticated Multi-Timeframe (MTF) confluence matrix, ADX-based chop filtering, and dynamic position sizing, making it a complete suite for methodical trade execution. Please note that if applied to non-standard charts (like Heikin Ashi or Renko), the script's calculations may repaint.
✨ Originality and Utility
Standard moving averages constantly adjust to new price data, which is useful for trailing trends but less effective for identifying historical break-and-retest zones. This script introduces a novel "Freeze Point" mechanic. At a specific, fixed date and time, the engine captures the exact values of four distinct moving averages and the Average True Range (ATR). These values are then projected forward as horizontal levels, creating a persistent architectural map of the market based on a fundamental historical event (like an earnings report, macroeconomic news release, or structural pivot). Combined with an Auto-Anchored VWAP that automatically initiates from this exact freeze date, it offers a highly unique, institutional-grade perspective on volumetric average price versus static historical momentum.
🔬 Methodology and Concepts
● Core Trend Identification
The indicator calculates four separate moving averages, with default lengths of 20, 50, 100, and 200.
Users can toggle the calculation method between Simple (SMA), Exponential (EMA), Weighted (WMA), and Volume-Weighted (VWMA) moving averages.
● The Freeze Engine
A timestamp is set by the user (defaulting to a specific date like "2025-12-31 23:59").
Once the market time crosses this threshold, the script triggers a state where calculations are locked.
It records the exact values of the four MAs and the 14-period ATR at that exact candle.
● Institutional Confluence and Risk Matrix
The script checks higher timeframe (HTF) trend alignment using a primary HTF filter (defaulting to Daily).
An optional MTF Matrix requires alignment across three custom timeframes (e.g., 240m, Daily, Weekly) before validating any bullish signals.
It incorporates an ADX threshold (default 20.0) to filter out choppy, ranging markets, ensuring signals are only generated during periods of active momentum.
🎨 Visual Guide
● Chart Overlays and Lines
MA 1 (Length 20): Plotted in bright Cyan (#00E5FF).
MA 2 (Length 50): Plotted in Teal (#14B5CB).
MA 3 (Length 100): Plotted in Royal Blue (#2979FF).
MA 4 (Length 200): Plotted in Purple (#AA00FF).
Freeze Marker: A vertical line (default Dashed, colored Gray/Blue) denotes the exact moment the historical levels were captured.
Anchored VWAP: If enabled, an Orange line (#FFB74D) plots the volume-weighted average price starting precisely from the Freeze Marker.
● Dynamic Liquidity Zones
If enabled, semi-transparent shaded bands appear around Frozen Level 1 and Frozen Level 4.
These bands represent a distance of 0.5 * Frozen ATR, illustrating expected volatility boundaries at the time of the freeze.
● Analytics Dashboard
A heads-up display table is drawn in the top-right corner, displaying a dark theme with blue/gray borders.
It lists the HTF Trend Status (Bullish in Green, Bearish in Red).
It displays the current Market State (Trending/Active vs. Chop/Low Vol) based on the ADX.
It shows current Volatility (ATR) and ADX Strength.
If enabled, it outlines the MTF Matrix Status and the mathematically calculated Dynamic Position Size.
● Signal Shapes and Labels
A green triangle pointing up (#00E676) plots below the bar when a valid Long signal is generated.
Dynamic labels attach to the right side of the frozen levels, constantly updating to show the MA length and exact price level.
📖 How to Use
● Setting the Anchor
Identify a major market event on your chart (a swing high/low, a CPI data release, or a sudden volume spike).
Open the settings and input the exact date and time of this event into the "Fixed Date/Time (Freeze Point)" input.
● Interpreting Signals
Wait for the market to interact with the freshly drawn horizontal frozen levels.
A valid Long signal (Green Triangle) will only trigger if: the price crosses above Frozen Level 1, the HTF trend is bullish, the market is not ranging (ADX > threshold), and the optional MTF matrix is fully aligned.
Monitor the Analytics Dashboard table to ensure the broader market environment supports the trade setup.
⚙️ Inputs and Settings
• Moving Average Settings
Length 1 through 4: Adjust the lookback periods for the core trend calculation.
MA Type: Dropdown to select the mathematical smoothing method (SMA, EMA, WMA, VWMA).
• Advanced Filters & Risk
Primary HTF Filter: Determines the baseline higher timeframe to establish the primary trend direction.
ADX Chop Filter Threshold: Sets the minimum ADX value required to consider the market "trending" rather than "ranging".
Risk/Reward Ratio: A multiplier used to automatically calculate Take Profit 1, 2, and 3 targets based on the dynamically calculated Stop Loss distance.
• Institutional Features (Optional)
Enable Auto-Anchored VWAP: Anchors a VWAP strictly starting from the chosen Freeze Date.
Enable MTF Confluence Matrix: Requires alignment across three separate, user-defined timeframes.
Enable Dynamic Position Sizing: Inputs for Account Size ($) and Risk Per Trade (%). The script uses the ATR-based stop loss to output exact contract/share sizing required to maintain strict risk parameters.
🔍 Deconstruction of the Underlying Scientific and Academic Framework
The TetraTrend Engine leverages several established quantitative and statistical concepts to derive its signals. Moving averages serve as low-pass filters, dampening high-frequency market noise to reveal the underlying directional component of the time series. By capturing these values statically at a user-defined vector (the Freeze Point), the script transitions from dynamic time-series analysis to fixed architectural support/resistance theory, positing that historical mean values at critical temporal nodes retain psychological and institutional relevance.
Furthermore, the integration of the Average Directional Index (ADX) relies on the statistical measurement of trend velocity and momentum dispersion. The ADX component acts as a volatility gatekeeper, mathematically ensuring that the standard deviation of directional movement exceeds a baseline threshold before capital is deployed. Position sizing calculations utilize the Average True Range (ATR)—a measure of absolute price dispersion—to dynamically scale risk exposure inversely to market volatility, ensuring normalized risk parity across varied market environments.
⚠️ Disclaimer
All provided scripts and indicators are strictly for educational exploration and must not be interpreted as financial advice or a recommendation to execute trades. I expressly disclaim all liability for any financial losses or damages that may result, directly or indirectly, from the reliance on or application of these tools. Market participation carries inherent risk where past performance never guarantees future returns, leaving all investment decisions and due diligence solely at your own discretion. インジケーター
Breakout Trend Bar AlertsEvery trend has a starting point. It's rarely a gradual drift — it's one massive, decisive candle that breaks the market out of consolidation and kicks off a sustained move. Breakout Bar Alerts is built to catch that exact moment.
The indicator monitors price action in real time and identifies when a bar forms that dwarfs everything around it — the largest high-to-low range of any candle in the last 250 bars. These are the bars where conviction enters the market, weak hands get flushed, and a new trend begins. When one appears, you get an instant alert so you're never late to the move.
Why these bars matter:
Big range bars represent a sudden surge of momentum and volume-backed commitment from one side of the market. Bulls or bears have taken control decisively. What follows is often the beginning of a trend leg — not a random spike.
Built to filter out the noise:
The opening bar of every session is excluded entirely. That first chaotic candle never skews your data or triggers a false signal.
Only bars within your active session window are counted. Off-hours price action is completely ignored, so your benchmark is always built from real, tradeable market conditions.
Three alert conditions — Bull Breakout Bar, Bear Breakout Bar, or Both — so you only get notified for the setups you actually trade.
Inputs:
Lookback Period — how many bars back to measure the largest range (default: 250)
Enable Time Filter — restricts detection and calculations to your active trading session
Active Session — define your session window in exchange time
Bull / Bear colors — fully customizable
Best used on intraday timeframes (1m – 15m) on futures, forex, or high-volume equities. When this fires, pay attention — the trend may already be starting. インジケーター
